Publications (Full List)

Categorised by venue , by year . 429 papers.

Google scholar (69440 citations) , DBLP , arXiv .

2024

Journal

  1. Towards robust monocular depth estimation: a new baseline and benchmark
    \(\cdot\) K. Xian, Z. Cao, C. Shen, G. Lin.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. End-to-end video text spotting with Transformer
    \(\cdot\) W. Wu, C. Shen, Y. Cai, D. Zhang, Y. Fu, P. Luo, H. Zhou.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

Conference

  1. PointAttN: you only need attention for point cloud completion
    \(\cdot\) J. Wang, Y. Cui, D. Guo, J. Li, Q. Liu, C. Shen.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Retrieval-augmented primitive representations for compositional zero-shot learning
    \(\cdot\) C. Jing, Y. Li, H. Chen, C. Shen.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Object-aware inversion and reassembly for image editing
    \(\cdot\) Z. Yang, D. Gui, W. Wang, H. Chen, B. Zhuang, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’24), 2024.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  4. De novo protein design using geometric vector field networks
    \(\cdot\) W. Mao, M. Zhu, Z. Sun, S. Shen, L. Wu, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’24), 2024.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

    1. Spotlight presentation.

  5. Matcher: segment anything with one shot using all-purpose feature matching
    \(\cdot\) Y. Liu, M. Zhu, H. Li, H. Chen, X. Wang, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’24), 2024.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

2023

Journal

  1. SegViT v2: exploring efficient and continual semantic segmentation with plain vision transformers
    \(\cdot\) B. Zhang, L. Liu, M. Phan, Z. Tian, C. Shen, Y. Liu.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  2. SPL-Net: spatial-semantic patch learning network for facial attribute recognition with limited labeled data
    \(\cdot\) Y. Yan, Y. Shu, S. Chen, J. Xue, C. Shen, H. Wang.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. From open set to closed set: supervised spatial divide-and-conquer for object counting
    \(\cdot\) H. Xiong, H. Lu, C. Liu, L. Liu, C. Shen, Z. Cao.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  4. A dynamic feature interaction framework for multi-task visual perception
    \(\cdot\) Y. Xi, H. Chen, N. Wang, P. Wang, Y. Zhang, C. Shen, Y. Liu.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. Super vision transformer
    \(\cdot\) M. Lin, M. Chen, Y. Zhang, C. Shen, R. Ji, L. Cao.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  6. SAI: an efficient and user-friendly tool for measurement of stomatal pores and density using deep computer vision
    \(\cdot\) N. Sai, J. Bockman, H. Chen, N. Watson-Haigh, B. Xu, X. Feng, A. Piechatzek, C. Shen, M. Gilliham.
    \(\cdot\) New Phytologist (NPH), 2023.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  7. Learning from partially labeled data for multi-organ and tumor segmentation
    \(\cdot\) Y. Xie, J. Zhang, Y. Xia, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  8. SC-DepthV3: robust self-supervised monocular depth estimation for dynamic scenes
    \(\cdot\) L. Sun, J. Bian, H. Zhan, W. Yin, I. Reid, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  9. SPTS v2: single-point scene text spotting
    \(\cdot\) Y. Liu, J. Zhang, D. Peng, M. Huang, X. Wang, J. Tang, C. Huang, D. Lin, C. Shen, X. Bai, L. Jin.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  10. Single-path bit sharing for automatic loss-aware model compression
    \(\cdot\) J. Liu, B. Zhuang, P. Chen, C. Shen, J. Cai, M. Tan.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

Conference

  1. FoPro: few-shot guided robust webly-supervised prototypical learning
    \(\cdot\) Y. Qin, X. Chen, C. Chen, Y. Shen, B. Ren, Y. Gu, J. Yang, C. Shen.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Point-Teaching: weakly semi-supervised object detection with point annotations
    \(\cdot\) Y. Ge, Q. Zhou, X. Wang, Z. Wang, H. Li, C. Shen.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Images speak in images: a generalist painter for in-context visual learning
    \(\cdot\) X. Wang, W. Wang, Y. Cao, C. Shen, T. Huang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  4. Learning conditional attributes for compositional zero-shot learning
    \(\cdot\) Q. Wang, L. Liu, C. Jing, H. Chen, G. Liang, P. Wang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. Segprompt: boosting open-world segmentation via category-level prompt learning
    \(\cdot\) M. Zhu, H. Li, H. Chen, C. Fan, W. Mao, C. Jing, Y. Liu, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  6. Generative prompt model for weakly supervised object localization
    \(\cdot\) Y. Zhao, Q. Ye, W. Wu, C. Shen, F. Wan.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  7. Robust geometry-preserving depth estimation using differentiable rendering
    \(\cdot\) C. Zhang, W. Yin, G. Yu, Z. Wang, T. Chen, B. Fu, J. Zhou, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. CTVIS: consistent training for online video instance segmentation
    \(\cdot\) K. Ying, Q. Zhong, W. Mao, Z. Wang, H. Chen, L. Wu, Y. Liu, C. Fan, Y. Zhuge, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  9. Metric3D: towards zero-shot metric 3d prediction from a single image
    \(\cdot\) W. Yin, C. Zhang, H. Chen, Z. Cai, G. Yu, K. Wang, X. Chen, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. Pose-free 3d scene reconstruction with frozen depth models
    \(\cdot\) G. Xu, W. Yin, H. Chen, C. Shen, K. Cheng, F. Zhao.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Diffumask: synthesizing images with pixel-level annotations for semantic segmentation using diffusion models
    \(\cdot\) W. Wu, Y. Zhao, M. Shou, H. Zhou, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. SegGPT: towards segmenting everything in context
    \(\cdot\) X. Wang, X. Zhang, Y. Cao, W. Wang, C. Shen, T. Huang.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Zolly: zoom focal length correctly for perspective-distorted human mesh reconstruction
    \(\cdot\) W. Wang, Y. Ge, H. Mei, Z. Cai, Q. Sun, C. Shen, Y. Wang, L. Yang, T. Komura.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  14. Conditional positional encodings for vision transformers
    \(\cdot\) X. Chu, Z. Tian, B. Zhang, X. Wang, X. Wei, H. Xia, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  15. Deep weakly-supervised anomaly detection
    \(\cdot\) G. Pang, C. Shen, H. Jin, A. van den Hengel.
    \(\cdot\) Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’23), 2023.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  16. DatasetDM: synthesizing data with perception annotations using diffusion models
    \(\cdot\) W. Wu, Y. Zhao, H. Chen, Y. Gu, R. Zhao, Y. He, H. Zhou, M. Shou, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’23), 2023.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

2022

Journal

  1. Effective eyebrow matting with domain adaptation
    \(\cdot\) L. Wang, H. Zhang, Q. Xiao, H. Xu, C. Shen, X. Jin.
    \(\cdot\) Computer Graphics Forum (CGF), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Structured binary neural networks for image recognition
    \(\cdot\) B. Zhuang, C. Shen, M. Tan, P. Chen, L. Liu, I. Reid.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. Arbitrarily shaped scene text detection with dynamic convolution
    \(\cdot\) Y. Cai, Y. Liu, C. L. Jin, Y. Li, D. Ergu.
    \(\cdot\) Pattern Recognition (PR), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. TSGB: target-selective gradient backprop for probing CNN visual saliency
    \(\cdot\) L. Cheng, P. Fang, Y. Liang, L. Zhang, C. Shen, H. Wang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. DeepEMD: differentiable earth mover's distance for few-shot learning
    \(\cdot\) C. Zhang, Y. Cai, G. Lin, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Towards accurate reconstruction of 3D scene shape from a single monocular image
    \(\cdot\) W. Yin, J. Zhang, O. Wang, S. Niklaus, S. Chen, Y. Liu, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  7. Instance and panoptic segmentation using conditional convolutions
    \(\cdot\) Z. Tian, B. Zhang, H. Chen, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  8. FCOS: a simple and strong anchor-free object detector
    \(\cdot\) Z. Tian, C. Shen, H. Chen, T. He.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholarproject webpage

  9. Dynamic convolution for 3D point cloud instance segmentation
    \(\cdot\) T. He, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. Improving monocular visual odometry using learned depth
    \(\cdot\) L. Sun, W. Yin, E. Xie, Z. Li, C. Sun, C. Shen.
    \(\cdot\) IEEE Transactions on Robotics (TRO), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. DenseCL: a simple framework for self-supervised dense visual pre-training
    \(\cdot\) X. Wang, R. Zhang, C. Shen, T. Kong.
    \(\cdot\) Visual Informatics (VI), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

Conference

  1. SPTS: single-point text spotting
    \(\cdot\) D. Peng, X. Wang, Y. Liu, J. Zhang, M. Huang, S. Lai, S. Zhu, J. Li, D. Lin, C. Shen, X. Bai, L. Jin.
    \(\cdot\) Proc. ACM International Conference on Multimedia (ACMMM’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. TopFormer: token pyramid transformer for mobile semantic segmentation
    \(\cdot\) W. Zhang, Z. Huang, G. Yu, T. Chen, G. Luo, X. Wang, W. Liu, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. FreeSOLO: learning to segment objects without annotations
    \(\cdot\) X. Wang, Z. Yu, S. De Mello, J. Kautz, A. Anandkumar, C. Shen, J. Alvarez.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  4. Retrieval augmented classification for long-tail visual recognition
    \(\cdot\) A. Long, W. Yin, T. Ajanthan, V. Nguyen, P. Purkait, R. Garg, A. Blair, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. RigidFlow: self-supervised scene flow learning on point clouds by local rigidity prior
    \(\cdot\) R. Li, C. Zhang, G. Lin, Z. Wang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  6. Catching both gray and black swans: open-set supervised anomaly detection
    \(\cdot\) C. Ding, G. Pan, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Boosting robustness of image matting with context assembling and strong data augmentation
    \(\cdot\) Y. Dai, B. Price, H. Zhang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  8. Poseur: direct human pose regression with transformers
    \(\cdot\) W. Mao, Y. Ge, C. Shen, Z. Tian, X. Wang, Z. Wang, A. van den Hengel.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  9. PointInst3D: segmenting 3D instances by points
    \(\cdot\) T. He, W. Yin, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. DisCo: remedying self-supervised learning on lightweight models with distilled contrastive learning
    \(\cdot\) Y. Gao, J. Zhuang, S. Lin, H. Cheng, X. Sun, K. Li, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  11. Efficient decoder-free object detection with transformers
    \(\cdot\) P. Chen, M. Zhang, Y. Shen, K. Sheng, Y. Gao, X. Sun, K. Li, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’22), 2022.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. DENSE: data-free one-shot federated learning
    \(\cdot\) J. Zhang, C. Chen, B. Li, L. Lyu, S. Wu, S. Ding, C. Shen, C. Wu.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  13. Hierarchical normalization for robust monocular depth estimation
    \(\cdot\) C. Zhang, W. Yin, Z. Wang, G. Yu, B. Fu, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  14. SegViT: semantic segmentation with plain vision transformers
    \(\cdot\) B. Zhang, Z. Tian, Q. Tang, X. Chu, X. Wei, C. Shen, Y. Liu.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  15. Fully convolutional one-stage 3D object detection on LiDAR range images
    \(\cdot\) Z. Tian, X. Chu, X. Wang, X. Wei, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  16. Text-adaptive multiple visual prototype matching for video-text retrieval
    \(\cdot\) C. Lin, A. Wu, J. Liang, J. Zhang, W. Ge, W. Zheng, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  17. Multi-dataset training of transformers for robust action recognition
    \(\cdot\) J. Liang, E. Zhang, J. Zhang, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  18. Adv-attribute: inconspicuous and transferable adversarial attack on face recognition
    \(\cdot\) S. Jia, B. Yin, T. Yao, S. Ding, C. Shen, X. Yang, C. Ma.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  19. PyramidCLIP: hierarchical feature alignment for vision-language model pretraining
    \(\cdot\) Y. Gao, J. Liu, Z. Xu, J. Zhang, K. Li, R. Ji, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’22), 2022.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

2021

Journal

  1. Memory-efficient hierarchical neural architecture search for image restoration
    \(\cdot\) H. Zhang, Y. Li, H. Chen, C. Gong, Z. Bai, C. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  2. BiSeNet v2: bilateral network with guided aggregation for real-time semantic segmentation
    \(\cdot\) C. Yu, C. Gao, J. Wang, G. Yu, C. Shen, N. Sang.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. A dual-attention-guided network for ghost-free high dynamic range imaging
    \(\cdot\) Q. Yan, D. Gong, Q. Shi, A. van den Hengel, C. Shen, I. Reid, Y. Zhang.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  4. NAS-FCOS: efficient search for object detection architectures
    \(\cdot\) N. Wang, Y. Gao, H. Chen, P. Wang, Z. Tian, C. Shen, Y. Zhang.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  5. Exploring the capacity of an orderless box discretization network for multi-orientation scene text detection
    \(\cdot\) Y. Liu, T. He, H. Chen, X. Wang, C. Luo, S. Zhang, C. Shen, L. Jin.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  6. Joint classification and regression for visual tracking with fully convolutional Siamese networks
    \(\cdot\) Y. Cui, D. Guo, Y. Shao, Z. Wang, C. Shen, L. Zhang, S. Chen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Unsupervised scale-consistent depth learning from video
    \(\cdot\) J. Bian, H. Zhan, N. Wang, Z. Li, L. Zhang, C. Shen, M. Cheng, I. Reid.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  8. Learning discriminative region representation for person retrieval
    \(\cdot\) Y. Zhao, X. Yu, Y. Gao, C. Shen.
    \(\cdot\) Pattern Recognition (PR), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Learning deep part-aware embedding for person retrieval
    \(\cdot\) Y. Zhao, C. Shen, X. Yu, H. Chen, Y. Gao, S. Xiong.
    \(\cdot\) Pattern Recognition (PR), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. An adversarial human pose estimation network injected with graph structure
    \(\cdot\) L. Tian, P. Wang, G. Liang, C. Shen.
    \(\cdot\) Pattern Recognition (PR), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Intra- and inter-pair consistency for semi-supervised gland segmentation
    \(\cdot\) Y. Xie, J. Zhang, Z. Liao, J. Verjans, C. Shen, Y. Xia.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. Effective training of convolutional neural networks with low-bitwidth weights and activations
    \(\cdot\) B. Zhuang, J. Liu, M. Tan, L. Liu, I. Reid, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Virtual normal: enforcing geometric constraints for accurate and robust depth prediction
    \(\cdot\) W. Yin, Y. Liu, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  14. SOLO: a simple framework for instance segmentation
    \(\cdot\) X. Wang, R. Zhang, C. Shen, T. Kong, L. Li.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  15. PAN++: towards efficient and accurate end-to-end spotting of arbitrarily-shaped text
    \(\cdot\) W. Wang, E. Xie, X. Li, X. Liu, D. Liang, Z. Yang, T. Lu, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  16. Towards end-to-end text spotting in natural scenes
    \(\cdot\) P. Wang, H. Li, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  17. ABCNet v2: adaptive bezier-curve network for real-time end-to-end text spotting
    \(\cdot\) Y. Liu, C. Shen, L. Jin, T. He, P. Chen, C. Liu, H. Chen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  18. Auto-rectify network for unsupervised indoor depth estimation
    \(\cdot\) J. Bian, H. Zhan, N. Wang, T. Chin, C. Shen, I. Reid.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

Conference

  1. Diverse knowledge distillation for end-to-end person search
    \(\cdot\) X. Zhang, X. Wang, J. Bian, C. Shen, M. You.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. SA-BNN: state-aware binary neural network
    \(\cdot\) C. Liu, P. Chen, B. Zhuang, C. Shen, B. Zhang, W. Ding.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Deep reasoning network for few-shot semantic segmentation
    \(\cdot\) Y. Zhuge, C. Shen.
    \(\cdot\) Proc. ACM International Conference on Multimedia (ACMMM’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Fully quantized image super-resolution networks
    \(\cdot\) H. Wang, P. Chen, B. Zhuang, C. Shen.
    \(\cdot\) Proc. ACM International Conference on Multimedia (ACMMM’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. DoDNet: learning to segment multi-organ and tumors from multiple partially labeled datasets
    \(\cdot\) J. Zhang, Y. Xie, Y. Xia, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  6. Learning to recover 3D scene shape from a single image
    \(\cdot\) W. Yin, J. Zhang, O. Wang, S. Niklaus, L. Mai, S. Chen, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Listed as one of the Best Paper Candidates, 32 out of about 6000 submissions.

  7. End-to-end video instance segmentation with Transformers
    \(\cdot\) Y. Wang, Z. Xu, X. Wang, C. Shen, B. Cheng, H. Shen, H. Xia.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  8. Dense contrastive learning for self-supervised visual pre-training
    \(\cdot\) X. Wang, R. Zhang, C. Shen, T. Kong, L. Li.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  9. BoxInst: high-performance instance segmentation with box annotations
    \(\cdot\) Z. Tian, C. Shen, X. Wang, H. Chen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  10. Learning spatial-semantic relationship for facial attribute recognition with limited labeled data
    \(\cdot\) Y. Shu, Y. Yan, S. Chen, J. Xue, C. Shen, H. Wang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Feature decomposition and reconstruction learning for effective facial expression recognition
    \(\cdot\) D. Ruan, Y. Yan, S. Lai, Z. Chai, C. Shen, H. Wang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. FCPose: fully convolutional multi-person pose estimation with dynamic instance-aware convolutions
    \(\cdot\) W. Mao, Z. Tian, X. Wang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  13. Generic perceptual loss for modelling structured output dependencies
    \(\cdot\) Y. Liu, W. Yin, Y. Chen, H. Chen, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  14. HCRF-Flow: scene flow from point clouds with continuous high-order CRFs and position-aware flow embedding
    \(\cdot\) R. Li, G. Lin, T. He, F. Liu, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  15. DyCo3D: robust instance segmentation of 3d point clouds through dynamic convolution
    \(\cdot\) T. He, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  16. Graph attention tracking
    \(\cdot\) D. Guo, Y. Shao, Y. Cui, Z. Wang, L. Zhang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  17. Learning affinity-aware upsampling for deep image matting
    \(\cdot\) Y. Dai, H. Lu, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  18. AQD: towards accurate quantized object detection
    \(\cdot\) P. Chen, J. Liu, B. Zhuang, M. Tan, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  19. Meta navigator: search for a good adaptation policy for few-shot learning
    \(\cdot\) C. Zhang, H. Ding, G. Lin, R. Li, C. Wang, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  20. A simple baseline for semi-supervised semantic segmentation with strong data augmentation
    \(\cdot\) J. Yuan, Y. Liu, C. Shen, Z. Wang, H. Li.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  21. BV-Person: a large-scale dataset for bird-view person re-identification
    \(\cdot\) C. Yan, G. Pang, L. Wang, J. Jiao, X. Feng, C. Shen, J. Li.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  22. Occluded person re-identification with single-scale global representations
    \(\cdot\) C. Yan, G. Pang, J. Jiao, X. Bai, X. Feng, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  23. Channel-wise knowledge distillation for dense prediction
    \(\cdot\) C. Shu, Y. Liu, J. Gao, L. Xu, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  24. FATNN: fast and accurate ternary neural networks
    \(\cdot\) P. Chen, B. Zhuang, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  25. FastFlowNet: a lightweight network for fast optical flow estimation
    \(\cdot\) L. Kong, C. Shen, J. Yang.
    \(\cdot\) Proc. International Conference on Robotics and Automation (ICRA’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  26. Toward deep supervised anomaly detection: reinforcement learning from partially labeled anomaly data
    \(\cdot\) G. Pang, A. van den Hengel, C. Shen, L. Cao.
    \(\cdot\) Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  27. CoTr: efficient 3D medical image segmentation by bridging CNN and transformer
    \(\cdot\) Y. Xie, J. Zhang, C. Shen, Y. Xia.
    \(\cdot\) Proc. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’21), 2021.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  28. Dynamic neural representational decoders for high-resolution semantic segmentation
    \(\cdot\) B. Zhang, Y. Liu, Z. Tian, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  29. Twins: revisiting the design of spatial attention in vision transformers
    \(\cdot\) X. Chu, Z. Tian, Y. Wang, B. Zhang, H. Ren, X. Wei, H. Xia, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’21), 2021.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

2020

Journal

  1. Deep learning for anomaly detection: a review
    \(\cdot\) G. Pang, C. Shen, L. Cao, A. van den Hengel.
    \(\cdot\) ACM Computing Surveys (ACMSurvey), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Towards light-weight portrait matting via parameter sharing
    \(\cdot\) Y. Dai, H. Lu, C. Shen.
    \(\cdot\) Computer Graphics Forum (CGF), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Separating content from style using adversarial learning for recognizing text in the wild
    \(\cdot\) C. Luo, Q. Lin, Y. Liu, L. Jin, C. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  4. TasselNetv2: in-field counting of wheat spikes with context-augmented local regression networks
    \(\cdot\) H. Xiong, Z. Cao, H. Lu, S. Madec, L. Liu, C. Shen.
    \(\cdot\) Plant Methods (PLME), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. MobileFAN: transferring deep hidden representation for face alignment
    \(\cdot\) Y. Zhao, Y. Liu, C. Shen, Y. Gao, S. Xiong.
    \(\cdot\) Pattern Recognition (PR), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Part-guided attention learning for vehicle instance retrieval
    \(\cdot\) X. Zhang, R. Zhang, J. Cao, D. Gong, M. You, C. Shen.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  7. A robust attentional framework for license plate recognition in the wild
    \(\cdot\) L. Zhang, P. Wang, H. Li, Z. Li, C. Shen, Y. Zhang.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. Real-time high-performance semantic image segmentation of urban street scenes
    \(\cdot\) G. Dong, Y. Yan, C. Shen, H. Wang.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Towards effective deep embedding for zero-shot learning
    \(\cdot\) L. Zhang, P. Wang, L. Liu, C. Shen, W. Wei, Y. Zhang, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. NSSNet: scale-aware object counting with non-scale suppression
    \(\cdot\) L. Liu, Z. Cao, H. Lu, H. Xiong, C. Shen.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Viral pneumonia screening on chest x-ray images using confidence-aware anomaly detection
    \(\cdot\) J. Zhang, Y. Xie, Z. Liao, G. Pang, J. Verjans, W. Li, Z. Sun, J. He, Y. Li, C. Shen, Y. Xia.
    \(\cdot\) IEEE Transactions on Medical Imaging (TMI), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. A mutual bootstrapping model for automated skin lesion segmentation and classification
    \(\cdot\) Y. Xie, J. Zhang, Y. Xia, C. Shen.
    \(\cdot\) IEEE Transactions on Medical Imaging (TMI), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. SESV: accurate medical image segmentation by predicting and correcting errors
    \(\cdot\) Y. Xie, J. Zhang, H. Lu, C. Shen, Y. Xia.
    \(\cdot\) IEEE Transactions on Medical Imaging (TMI), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  14. OPMP: an omni-directional pyramid mask proposal network for arbitrary-shape scene text detection
    \(\cdot\) S. Zhang, Y. Liu, L. Jin, Z. Wei, C. Shen.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  15. Joint deep learning of facial expression synthesis and recognition
    \(\cdot\) Y. Yan, Y. Huang, S. Chen, C. Shen, H. Wang.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  16. Accurate tensor completion via adaptive low-rank representation
    \(\cdot\) L. Zhang, W. Wei, Q. Shi, C. Shen, A. van den Hengel, Y. Zhang.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  17. Deep clustering with sample-assignment invariance prior
    \(\cdot\) X. Peng, H. Zhu, J. Feng, C. Shen, H. Zhang, J. Zhou.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  18. Learning deep gradient descent optimization for image deconvolution
    \(\cdot\) D. Gong, Z. Zhang, Q. Shi, A. van den Hengel, C. Shen, Y. Zhang.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  19. Real-time image smoothing via iterative least squares
    \(\cdot\) W. Liu, P. Zhang, X. Huang, J. Yang, C. Shen, I. Reid.
    \(\cdot\) ACM Transactions on Graphics (TOG), 2020.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  20. Plenty is plague: fine-grained learning for visual question answering
    \(\cdot\) Y. Zhou, R. Ji, J. Su, X. Sun, D. Meng, Y. Gao, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  21. Ordered or orderless: a revisit for video based person re-identification
    \(\cdot\) L. Zhang, Z. Shi, J. Zhou, M. Cheng, Y. Liu, J. Bian, Z. Zeng, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  22. Index networks
    \(\cdot\) H. Lu, Y. Dai, C. Shen, S. Xu.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  23. Structured knowledge distillation for dense prediction
    \(\cdot\) Y. Liu, C. Shun, J. Wang, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  24. Adversarial learning of structure-aware fully convolutional networks for landmark localization
    \(\cdot\) Y. Chen, C. Shen, H. Chen, X. Wei, L. Liu, J. Yang.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  25. Improving generative adversarial networks with local coordinate coding
    \(\cdot\) J. Cao, Y. Guo, Q. Wu, C. Shen, J. Huang, M. Tan.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

Conference

  1. Task-aware monocular depth estimation for 3D object detection
    \(\cdot\) X. Wang, W. Yin, T. Kong, Y. Jiang, L. Li, C. Shen.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. V-PROM: a benchmark for visual reasoning using visual progressive matrices
    \(\cdot\) D. Teney, P. Wang, J. Cao, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. Training quantized neural networks with a full-precision auxiliary module
    \(\cdot\) B. Zhuang, L. Liu, M. Tan, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  4. Mask encoding for single shot instance segmentation
    \(\cdot\) R. Zhang, Z. Tian, C. Shen, M. You, Y. Yan.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  5. Memory-efficient hierarchical neural architecture search for image denoising
    \(\cdot\) H. Zhang, Y. Li, H. Chen, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. DeepEMD: few-shot image classification with differentiable earth mover's distance and structured classifiers
    \(\cdot\) C. Zhang, Y. Cai, G. Lin, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  7. Context prior for scene segmentation
    \(\cdot\) C. Yu, J. Wang, C. Gao, G. Yu, C. Shen, N. Sang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  8. PolarMask: single shot instance segmentation with polar representation
    \(\cdot\) E. Xie, P. Sun, X. Song, W. Wang, X. Liu, D. Liang, C. Shen, P. Luo.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  9. On the general value of evidence, and bilingual scene-text visual question answering
    \(\cdot\) X. Wang, Y. Liu, C. Shen, C. Ng, C. Luo, L. Jin, C. Chan, A. van den Hengel, L. Wang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. NAS-FCOS: fast neural architecture search for object detection
    \(\cdot\) N. Wang, Y. Gao, H. Chen, P. Wang, Z. Tian, C. Shen, Y. Zhang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  11. REVERIE: remote embodied visual referring expression in real indoor environments
    \(\cdot\) Y. Qi, Q. Wu, P. Anderson, X. Wang, W. Wang, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  12. Self-trained deep ordinal regression for end-to-end video anomaly detection
    \(\cdot\) G. Pang, C. Yan, C. Shen, A. van den Hengel, X. Bai.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. ABCNet: arbitrarily-shaped scene text spotting with adaptive Bezier-curve network in real time
    \(\cdot\) Y. Liu, H. Chen, C. Shen, T. He, L. Jin, L. Wang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  14. BlendMask: top-down meets bottom-up for instance segmentation
    \(\cdot\) H. Chen, K. Sun, Z. Tian, C. Shen, Y. Huang, Y. Yan.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  15. Representative graph neural network
    \(\cdot\) C. Yu, Y. Liu, C. Gao, C. Shen, N. Sang.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  16. Segmenting transparent objects in the wild
    \(\cdot\) E. Xie, W. Wang, W. Wang, M. Ding, C. Shen, P. Luo.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  17. SOLO: segmenting objects by locations
    \(\cdot\) X. Wang, T. Kong, C. Shen, Y. Jiang, L. Li.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  18. Scene text image super-resolution in the wild
    \(\cdot\) W. Wang, E. Xie, X. Liu, W. Wang, D. Liang, C. Shen, X. Bai.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  19. AE TextSpotter: learning visual and linguistic representation for ambiguous text spotting
    \(\cdot\) W. Wang, X. Liu, X. Ji, E. Xie, D. Liang, Z. Yang, T. Lu, C. Shen, P. Luo.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  20. Soft expert reward learning for vision-and-language navigation
    \(\cdot\) H. Wang, Q. Wu, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  21. Conditional convolutions for instance segmentation
    \(\cdot\) Z. Tian, C. Shen, H. Chen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

  22. Efficient semantic video segmentation with per-frame inference
    \(\cdot\) Y. Liu, C. Shen, C. Yu, J. Wang.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  23. Weighing counts: sequential crowd counting by reinforcement learning
    \(\cdot\) L. Liu, H. Lu, H. Zou, H. Xiong, Z. Cao, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  24. Instance-aware embedding for point cloud instance segmentation
    \(\cdot\) T. He, Y. Liu, C. Shen, X. Wang, C. Sun.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  25. Learning and memorizing representative prototypes for 3D point cloud semantic and instance segmentation
    \(\cdot\) T. He, D. Gong, Z. Tian, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’20), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  26. Unsupervised representation learning by predicting random distances
    \(\cdot\) H. Wang, G. Pang, C. Shen, C. Ma.
    \(\cdot\) Proc. International Joint Conferences on Artificial Intelligence (IJCAI’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  27. Pairwise relation learning for semi-supervised gland segmentation
    \(\cdot\) Y. Xie, J. Zhang, Z. Liao, C. Shen, J. Verjans, Y. Xia.
    \(\cdot\) Proc. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’20), 2020.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  28. SOLOv2: dynamic and fast instance segmentation
    \(\cdot\) X. Wang, R. Zhang, T. Kong, L. Li, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’20), 2020.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

2019

Journal

  1. Adaptive importance learning for improving lightweight image super-resolution network
    \(\cdot\) L. Zhang, P. Wang, C. Shen, L. Liu, W. Wei, Y. Zhang, A. van den Hengel.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  2. Accurate imagery recovery using a multi-observation patch model
    \(\cdot\) L. Zhang, W. Wei, Q. Shen, C. Shen, A. van den Hengel.
    \(\cdot\) Information Sciences (IS), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Heritage image annotation via collective knowledge
    \(\cdot\) J. Zhang, Q. Wu, J. Zhang, C. Shen, J. Lu, Q. Wu.
    \(\cdot\) Pattern Recognition (PR), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Wider or deeper: revisiting the ResNet model for visual recognition
    \(\cdot\) Z. Wu, C. Shen, A. van den Hengel.
    \(\cdot\) Pattern Recognition (PR), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. Order-aware convolutional pooling for video based action recognition
    \(\cdot\) P. Wang, L. Liu, C. Shen, H. Shen.
    \(\cdot\) Pattern Recognition (PR), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  6. Structural analysis of attributes for vehicle re-identification and retrieval
    \(\cdot\) Y. Zhao, C. Shen, H. Wang, S. Chen.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Human detection aided by deeply learned semantic masks
    \(\cdot\) X. Wang, C. Shen, H. Li, S. Xu.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. Embedding bilateral filter in least squares for efficient edge-preserving image smoothing
    \(\cdot\) W. Liu, P. Zhang, X. Chen, C. Shen, X. Huang, J. Yang.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Counting objects by blockwise classification
    \(\cdot\) L. Liu, H. Lu, H. Xiong, K. Xian, Z. Cao, C. Shen.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. Hyperspectral classification based on lightweight 3D-CNN with transfer learning
    \(\cdot\) H. Zhang, Y. Li, Y. Jiang, P. Wang, Q. Shen, C. Shen.
    \(\cdot\) IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Salient object detection with lossless feature reflection and weighted structural loss
    \(\cdot\) P. Zhang, W. Liu, H. Lu, C. Shen.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. Piecewise classifier mappings: learning fine-grained learners for novel categories with few examples
    \(\cdot\) X. Wei, P. Wang, L. Liu, C. Shen, J. Wu.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Multiple instance learning with emerging novel class
    \(\cdot\) X. Wei, H. Ye, X. Mu, J. Wu, C. Shen, Z. Zhou.
    \(\cdot\) IEEE Transactions on Knowledge and Data Engineering (TKDE), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  14. Attention residual learning for skin lesion classification
    \(\cdot\) J. Zhang, Y. Xie, Y. Xia, C. Shen.
    \(\cdot\) IEEE Transactions on Medical Imaging (TMI), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  15. Decoupled spatial neural attention for weakly supervised semantic segmentation
    \(\cdot\) T. Zhang, G. Lin, J. Cai, T. Shen, C. Shen, A. Kot.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  16. RefineNet: multi-path refinement networks for dense prediction
    \(\cdot\) G. Lin, F. Liu, A. Milan, C. Shen, I. Reid.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholarproject webpage

    1. Pytorch code is here.

Conference

  1. Show, attend and read: a simple and strong baseline for irregular text recognition
    \(\cdot\) H. Li, P. Wang, C. Shen, G. Zhang.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Deep hashing by discriminating hard examples
    \(\cdot\) C. Yan, G. Pang, X. Bai, C. Shen, J. Zhou, E. Hancock.
    \(\cdot\) Proc. ACM International Conference on Multimedia (ACMMM’19), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Structured binary neural networks for accurate image classification and semantic segmentation
    \(\cdot\) B. Zhuang, C. Shen, M. Tan, L. Liu, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  4. Mind your neighbours: image annotation with metadata neighbourhood graph co-attention networks
    \(\cdot\) J. Zhang, Q. Wu, J. Zhang, C. Shen, J. Lu.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  5. CANet: class-agnostic segmentation networks with iterative refinement and attentive few-shot learning
    \(\cdot\) C. Zhang, G. Lin, F. Liu, R. Yao, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Attention-guided network for ghost-free high dynamic range imaging
    \(\cdot\) Q. Yan, D. Gong, Q. Shi, A. van den Hengel, C. Shen, I. Reid, Y. Zhang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  7. Associatively segmenting instances and semantics in point clouds
    \(\cdot\) X. Wang, S. Liu, X. Shen, C. Shen, J. Jia.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  8. Neighbourhood watch: referring expression comprehension via language-guided graph attention networks
    \(\cdot\) P. Wang, Q. Wu, J. Cao, C. Shen, L. Gao, A. vanden Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  9. Decoders matter for semantic segmentation: data-dependent decoding enables flexible feature aggregation
    \(\cdot\) Z. Tian, T. He, C. Shen, Y. Yan.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. Fast neural architecture search of compact semantic segmentation models via auxiliary cells
    \(\cdot\) V. Nekrasov, H. Chen, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  11. Visual question answering as reading comprehension
    \(\cdot\) H. Li, P. Wang, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. Knowledge adaptation for efficient semantic segmentation
    \(\cdot\) T. He, C. Shen, Z. Tian, D. Gong, C. Sun, Y. Yan.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Self-training with progressive augmentation for unsupervised cross-domain person re-identification
    \(\cdot\) X. Zhang, J. Cao, C. Shen, M. You.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  14. Exploiting temporal consistency for real-time video depth estimation
    \(\cdot\) H. Zhang, C. Shen, Y. Li, Y. Cao, Y. Liu, Y. Yan.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  15. Enforcing geometric constraints of virtual normal for depth prediction
    \(\cdot\) W. Yin, Y. Liu, C. Shen, Y. Yan.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  16. From open set to closed set: counting objects by spatial divide-and-conquer
    \(\cdot\) H. Xiong, H. Lu, C. Liu, L. Liu, Z. Cao, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  17. Efficient and accurate arbitrary-shaped text detection with pixel aggregation network
    \(\cdot\) W. Wang, E. Xie, X. Song, Y. Zang, W. Wang, T. Lu, G. Yu, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  18. FCOS: fully convolutional one-stage object detection
    \(\cdot\) Z. Tian, C. Shen, H. Chen, T. He.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  19. Indices matter: learning to index for deep image matting
    \(\cdot\) H. Lu, Y. Dai, C. Shen, S. Xu.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  20. Real-time joint semantic segmentation and depth estimation using asymmetric annotations
    \(\cdot\) V. Nekrasov, T. Dharmasiri, A. Spek, T. Drummond, C. Shen, I. Reid.
    \(\cdot\) Proc. International Conference on Robotics and Automation (ICRA’19), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  21. Light-weight hybrid convolutional network for liver tumor segmentation
    \(\cdot\) J. Zhang, Y. Xie, P. Zhang, H. Chen, Y. Xia, C. Shen.
    \(\cdot\) Proc. International Joint Conference on Artificial Intelligence (IJCAI’19), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  22. Deep anomaly detection with deviation networks
    \(\cdot\) G. Pang, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD’19), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  23. Deep segmentation-emendation model for gland instance segmentation
    \(\cdot\) Y. Xie, H. Lu, J. Zhang, C. Shen, Y. Xia.
    \(\cdot\) Proc. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’19), 2019.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  24. Multi-marginal wasserstein GAN
    \(\cdot\) J. Cao, L. Mo, Y. Zhang, K. Jia, C. Shen, M. Tan.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  25. Unsupervised scale-consistent depth and ego-motion learning from monocular video
    \(\cdot\) J. Bian, Z. Li, N. Wang, H. Zhan, C. Shen, M. Cheng, I. Reid.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’19), 2019.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

2018

Journal

  1. Cluster sparsity field: an internal hyperspectral imagery prior for reconstruction
    \(\cdot\) L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2018.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  2. Reading car license plates using deep neural networks
    \(\cdot\) H. Li, P. Wang, M. You, C. Shen.
    \(\cdot\) Image and Vision Computing (IVC), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. Multi-label learning based deep transfer neural network for facial attribute classification
    \(\cdot\) N. Zhuang, Y. Yan, S. Chen, H. Wang, C. Shen.
    \(\cdot\) Pattern Recognition (PR), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  4. Unsupervised object discovery and co-localization by deep descriptor transforming
    \(\cdot\) X. Wei, C. Zhang, J. Wu, C. Shen, Z. Zhou.
    \(\cdot\) Pattern Recognition (PR), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. An extended filtered channel framework for pedestrian detection
    \(\cdot\) M. You, Y. Zhang, C. Shen, X. Zhang.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  6. Towards end-to-end car license plates detection and recognition with deep neural networks
    \(\cdot\) H. Li, P. Wang, C. Shen.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Unsupervised domain adaptation using robust class-wise matching
    \(\cdot\) L. Zhang, P. Wang, W. Wei, H. Lu, C. Shen, A. van den Hengel, Y. Zhang.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. Semantics-aware visual object tracking
    \(\cdot\) R. Yao, G. Lin, C. Shen, Y. Zhang, Q. Shi.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Pushing the limits of deep CNNs for pedestrian detection
    \(\cdot\) Q. Hu, P. Wang, C. Shen, A. van den Hengel, F. Porikli.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. An embarrassingly simple approach to visual domain adaptation
    \(\cdot\) H. Lu, C. Shen, Z. Cao, Y. Xiao, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  11. Multi-label image classification with regional latent semantic dependencies
    \(\cdot\) J. Zhang, Q. Wu, C. Shen, J. Zhang, J. Lu.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. Automatic image cropping for visual aesthetic enhancement using deep neural networks and cascaded regression
    \(\cdot\) G. Guo, H. Wang, C. Shen, Y. Yan, H. Liao.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. FVQA: fact-based visual question answering
    \(\cdot\) P. Wang, Q. Wu, C. Shen, A. Dick, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  14. Ordinal constraint binary coding for approximate nearest neighbor search
    \(\cdot\) H. Liu, R. Ji, J. Wang, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2018.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

Conference

  1. HCVRD: a benchmark for large-scale human-centered visual relationship detection
    \(\cdot\) B. Zhuang, Q. Wu, C. Shen, I. Reid, A. van den Hengel.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Kill two birds with one stone: weakly-supervised neural network for image annotation and tag refinement
    \(\cdot\) J. Zhang, Q. Wu, J. Zhang, C. Shen, J. Lu.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Coarse-to-fine: a RNN-based hierarchical attention model for vehicle re-identification
    \(\cdot\) X. Wei, C. Zhang, L. Liu, C. Shen, J. Wu.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Deep attention-based classification network for robust depth prediction
    \(\cdot\) R. Li, K. Xian, C. Shen, Z. Cao, H. Lu, L. Hang.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. Light-weight refinenet for real-time semantic segmentation
    \(\cdot\) V. Nekrasov, C. Shen, I. Reid.
    \(\cdot\) Proc. British Machine Vision Conference (BMVC’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  6. A hybrid probabilistic model for camera relocalization
    \(\cdot\) M. Cai, C. Shen, I. Reid.
    \(\cdot\) Proc. British Machine Vision Conference (BMVC’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Parallel attention: a unified framework for visual object discovery through dialogs and queries
    \(\cdot\) B. Zhuang, Q. Wu, C. Shen, I. Reid, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  8. Towards effective low-bitwidth convolutional neural networks
    \(\cdot\) B. Zhuang, C. Shen, M. Tan, L. Liu, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  9. Monocular relative depth perception with web stereo data supervision
    \(\cdot\) K. Xian, C. Shen, Z. Cao, H. Lu, Y. Xiao, R. Li, Z. Luo.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. Are you talking to me? reasoned visual dialog generation through adversarial learning
    \(\cdot\) Q. Wu, P. Wang, C. Shen, I. Reid, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  11. Repulsion loss: detecting pedestrians in a crowd
    \(\cdot\) X. Wang, T. Xiao, Y. Jiang, S. Shao, J. Sun, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

    1. Others have implemented our paper: Repulsion loss in SSD and Repulsion loss in RetinaNet.

  12. VITAL: visual tracking via adversarial learning
    \(\cdot\) Y. Song, C. Ma, X. Wu, L. Gong, L. Bao, W. Zuo, C. Shen, R. Lau, M. Yang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  13. Bootstrapping the performance of webly supervised semantic segmentation
    \(\cdot\) T. Shen, G. Lin, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  14. Visual question answering with memory-augmented networks
    \(\cdot\) C. Ma, C. Shen, A. Dick, Q. Wu, P. Wang, A. van den Hengel, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  15. An end-to-end textspotter with explicit alignment and attention
    \(\cdot\) T. He, Z. Tian, W. Huang, C. Shen, Y. Qiao, C. Sun.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  16. FSRNet: end-to-end learning face super-resolution with facial priors
    \(\cdot\) Y. Chen, Y. Tai, X. Liu, C. Shen, J. Yang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  17. Goal-oriented visual question generation via intermediate rewards
    \(\cdot\) J. Zhang, Q. Wu, C. Shen, J. Zhang, J. Lu, A. van den Hengel.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  18. Learning to predict crisp boundaries
    \(\cdot\) R. Deng, C. Shen, S. Liu, H. Wang, X. Liu.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  19. Learning deep representations using convolutional auto-encoders with symmetric skip connections
    \(\cdot\) L. Dong, Y. Gan, X. Mao, Y. Yang, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  20. Adversarial learning with local coordinate coding
    \(\cdot\) J. Cao, Y. Guo, Q. Wu, C. Shen, J. Huang, M. Tan.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  21. Salient object detection by lossless feature reflection
    \(\cdot\) P. Zhang, W. Liu, H. Lu, C. Shen.
    \(\cdot\) Proc. International Joint Conference on Artificial Intelligence (IJCAI’18), 2018.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

2017

Journal

  1. Visual question answering: a survey of methods and datasets
    \(\cdot\) Q. Wu, D. Teney, P. Wang, C. Shen, A. Dick, A. van den Hengel.
    \(\cdot\) Computer Vision and Image Understanding (CVIU), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Structured learning of binary codes with column generation for optimizing ranking measures
    \(\cdot\) G. Lin, F. Liu, C. Shen, J. Wu, H. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  3. Removal of optically thick clouds from high-resolution satellite imagery using dictionary group learning and interdictionary nonlocal joint sparse coding
    \(\cdot\) Y. Li, W. Li, C. Shen.
    \(\cdot\) IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTAEORS), 2017.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. TasselNet: counting maize tassels in the wild via local counts regression network
    \(\cdot\) H. Lu, Z. Cao, Y. Xiao, B. Zhuang, C. Shen.
    \(\cdot\) Plant Methods (PLME), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. Deep linear discriminant analysis on Fisher networks: a hybrid architecture for person re-identification
    \(\cdot\) L. Wu, C. Shen, A. van den Hengel.
    \(\cdot\) Pattern Recognition (PR), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Mask-CNN: localizing parts and selecting descriptors for bird species categorization
    \(\cdot\) X. Wei, C. Xie, J. Wu, C. Shen.
    \(\cdot\) Pattern Recognition (PR), 2017.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Learning discriminative trajectorylet detector sets for accurate skeleton-based action recognition
    \(\cdot\) R. Qiao, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Pattern Recognition (PR), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  8. Deep CNNs with spatially weighted pooling for fine-grained car recognition
    \(\cdot\) Q. Hu, H. Wang, T. Li, C. Shen.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2017.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Crowd counting via weighted VLAD on dense attribute feature maps
    \(\cdot\) B. Sheng, C. Shen, G. Lin, J. Li, W. Yang, C. Sun.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. Estimating depth from monocular images as classification using deep fully convolutional residual networks
    \(\cdot\) Y. Cao, Z. Wu, C. Shen.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  11. Discriminative training of deep fully-connected continuous CRF with task-specific loss
    \(\cdot\) F. Liu, G. Lin, C. Shen.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. Exploiting depth from single monocular images for object detection and semantic segmentation
    \(\cdot\) Y. Cao, C. Shen, H. Shen.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Structured learning of tree potentials in CRF for image segmentation
    \(\cdot\) F. Liu, G. Lin, R. Qiao, C. Shen.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  14. Image captioning and visual question answering based on attributes and external knowledge
    \(\cdot\) Q. Wu, C. Shen, P. Wang, A. Dick, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  15. Compositional model based Fisher vector coding for image classification
    \(\cdot\) L. Liu, P. Wang, C. Shen, L. Wang, A. van den Hengel, C. Wang, H. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  16. Cross-convolutional-layer pooling for image recognition
    \(\cdot\) L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  17. Exploring context with deep structured models for semantic segmentation
    \(\cdot\) G. Lin, C. Shen, A. van den Hengel, I. Reid.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

Conference

  1. Auxiliary tasks to improve trip hazard affordance detection
    \(\cdot\) S. McMahon, T. Shen, N. Sunderhauf, I. Reid, C. Shen, M. Milford.
    \(\cdot\) Proc. Australasian Conference on Robotics and Automation (ACRA’17), 2017.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Weakly supervised semantic segmentation based on co-segmentation
    \(\cdot\) T. Shen, G. Lin, L. Liu, C. Shen, I. Reid.
    \(\cdot\) Proc. British Machine Vision Conference (BMVC’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. Visually aligned word embeddings for improving zero-shot learning
    \(\cdot\) R. Qiao, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. British Machine Vision Conference (BMVC’17), 2017.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Attend in groups: a weakly-supervised deep learning framework for learning from web data
    \(\cdot\) B. Zhuang, L. Liu, Y. Li, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. The VQA-machine: learning how to use existing vision algorithms to answer new questions
    \(\cdot\) P. Wang, Q. Wu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Multi-attention network for one shot learning
    \(\cdot\) P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, H. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  7. RefineNet: multi-path refinement networks for high-resolution semantic segmentation
    \(\cdot\) G. Lin, A. Milan, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Light-weight RefineNet with Pytorch code.

  8. Sequential person recognition in photo albums with a recurrent network
    \(\cdot\) Y. Li, G. Lin, B. Zhuang, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  9. From motion blur to motion flow: a deep learning solution for removing heterogeneous motion blur
    \(\cdot\) D. Gong, J. Yang, L. Liu, Y. Zhang, I. Reid, C. Shen, A. van den Hengel, Q. Shi.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. Towards context-aware interaction recognition
    \(\cdot\) B. Zhuang, L. Liu, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  11. When unsupervised domain adaptation meets tensor representations
    \(\cdot\) H. Lu, L. Zhang, Z. Cao, W. Wei, K. Xian, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. Semi-global weighted least squares in image filtering
    \(\cdot\) W. Liu, X. Chen, C. Shen, Z. Liu, J. Yang.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Towards end-to-end text spotting with convolutional recurrent neural networks
    \(\cdot\) H. Li, P. Wang, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  14. Adversarial PoseNet: a structure-aware convolutional network for human pose estimation
    \(\cdot\) Y. Chen, C. Shen, X. Wei, L. Liu, J. Yang.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  15. Deep learning features at scale for visual place recognition
    \(\cdot\) Z. Chen, A. Jacobson, N. Sunderhauf, B. Upcroft, L. Liu, C. Shen, I. Reid, M. Milford.
    \(\cdot\) Proc. IEEE International Conference on Robotics and Automation (ICRA’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  16. Deep descriptor transforming for image co-localization
    \(\cdot\) X. Wei, C. Zhang, Y. Li, C. Xie, J. Wu, C. Shen, Z. Zhou.
    \(\cdot\) Proc. International Joint Conference on Artificial Intelligence (IJCAI’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  17. Explicit knowledge-based reasoning for visual question answering
    \(\cdot\) P. Wang, Q. Wu, C. Shen, A. van den Hengel, A. Dick.
    \(\cdot\) Proc. International Joint Conference on Artificial Intelligence (IJCAI’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  18. Learning multi-level region consistency with dense multi-label networks for semantic segmentation
    \(\cdot\) T. Shen, G. Lin, C. Shen, I. Reid.
    \(\cdot\) Proc. International Joint Conference on Artificial Intelligence (IJCAI’17), 2017.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

2016

Journal

  1. Structured learning of metric ensembles with application to person re-identification
    \(\cdot\) S. Paisitkriangkrai, L. Wu, C. Shen, A. van den Hengel.
    \(\cdot\) Computer Vision and Image Understanding (CVIU), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Unsupervised feature learning for dense correspondences across scenes
    \(\cdot\) C. Zhang, C. Shen, T. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  3. Efficient semidefinite branch-and-cut for MAP-MRF inference
    \(\cdot\) P. Wang, C. Shen, A. van den Hengel, P. Torr.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  4. Mining mid-level visual patterns with deep CNN activations
    \(\cdot\) Y. Li, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  5. Online unsupervised feature learning for visual tracking
    \(\cdot\) F. Liu, C. Shen, I. Reid, A. van den Hengel.
    \(\cdot\) Image and Vision Computing (IVC), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Canonical principal angles correlation analysis for two-view data
    \(\cdot\) S. Wang, J. Lu, X. Gu, C. Shen, R. Xia, J. Yang.
    \(\cdot\) Journal of Visual Communication and Image Representation (JVCIR), 2016.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  7. Face image classification by pooling raw features
    \(\cdot\) F. Shen, C. Shen, X. Zhou, Y. Yang, H. Shen.
    \(\cdot\) Pattern Recognition (PR), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  8. Face recognition using linear representation ensembles
    \(\cdot\) H. Li, F. Shen, C. Shen, Y. Yang, Y. Gao.
    \(\cdot\) Pattern Recognition (PR), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  9. Fast detection of multiple objects in traffic scenes with a common detection framework
    \(\cdot\) Q. Hu, S. Paisitkriangkrai, C. Shen, A. van den Hengel, F. Porikli.
    \(\cdot\) IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2016.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. Part-based robust tracking using online latent structured learning
    \(\cdot\) R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2016.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  11. Temporal pyramid pooling based convolutional neural network for action recognition
    \(\cdot\) P. Wang, Y. Cao, C. Shen, L. Liu, H. Shen.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  12. Dictionary learning for promoting structured sparsity in hyerpsectral compressive sensing
    \(\cdot\) L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi.
    \(\cdot\) IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2016.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  13. Scalable linear visual feature learning via online parallel nonnegative matrix factorization
    \(\cdot\) X. Zhao, X. Li, Z. Zhang, C. Shen, L. Gao, X. Li.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2016.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  14. Large-scale binary quadratic optimization using semidefinite relaxation and applications
    \(\cdot\) P. Wang, C. Shen, A. van den Hengel, P. Torr.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  15. Pedestrian detection with spatially pooled features and structured ensemble learning
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  16. A generalized probabilistic framework for compact codebook creation
    \(\cdot\) L. Liu, L. Wang, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  17. Learning depth from single monocular images using deep convolutional neural fields
    \(\cdot\) F. Liu, C. Shen, G. Lin, I. Reid.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  18. Online metric-weighted linear representations for robust visual tracking
    \(\cdot\) X. Li, C. Shen, A. Dick, Z. Zhang, Y. Zhuang.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

Conference

  1. Fast training of triplet-based deep binary embedding networks
    \(\cdot\) B. Zhuang, G. Lin, C. Shen, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  2. Ask me anything: free-form visual question answering based on knowledge from external sources
    \(\cdot\) Q. Wu, P. Wang, C. Shen, A. Dick, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. What value do explicit high level concepts have in vision to language problems
    \(\cdot\) Q. Wu, C. Shen, L. Liu, A. Dick, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  4. What's wrong with that object? identifying irregular object from images by modelling the detection score distribution
    \(\cdot\) P. Wang, L. Liu, C. Shen, Z. Huang, A. van den Hengel, H. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. Less is more: zero-shot learning from online textual documents with noise suppression
    \(\cdot\) R. Qiao, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Efficient piecewise training of deep structured models for semantic segmentation
    \(\cdot\) G. Lin, C. Shen, A. van dan Hengel, I. Reid.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  7. Cluster sparsity field for hyperspectral imagery denoising
    \(\cdot\) L. Zhang, W. Wei, Y. Zhang, C. Shen, A. van den Hengel, Q. Shi.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’16), 2016.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. Image co-localization by mimicking a good detector's confidence score distribution
    \(\cdot\) Y. Li, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’16), 2016.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  9. Image restoration using very deep fully convolutional encoder-decoder networks with symmetric skip connections
    \(\cdot\) X. Mao, C. Shen, Y. Yang.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’16), 2016.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

    1. Others have implemented our paper.

2015

Journal

  1. Extrinsic methods for coding and dictionary learning on Grassmann manifolds
    \(\cdot\) M. Harandi, R. Hartley, C. Shen, B. Lovell, C. Sanderson.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  2. CRF learning with CNN features for image segmentation
    \(\cdot\) F. Liu, G. Lin, C. Shen.
    \(\cdot\) Pattern Recognition (PR), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  3. Hashing on nonlinear manifolds
    \(\cdot\) F. Shen, C. Shen, Q. Shi, A. van den Hengel, Z. Tang, H. Shen.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  4. A computational model of the short-cut rule for 2D shape decomposition
    \(\cdot\) L. Luo, C. Shen, X. Liu, C. Zhang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. Worst-case linear discriminant analysis as scalable semidefinite feasibility problems
    \(\cdot\) H. Li, C. Shen, A. van den Hengel, Q. Shi.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  6. Supervised hashing using graph cuts and boosted decision trees
    \(\cdot\) G. Lin, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

Conference

  1. Efficient SDP inference for fully-connected CRFs based on low-rank decomposition
    \(\cdot\) P. Wang, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Learning graph structure for multi-label image classification via clique generation
    \(\cdot\) M. Tan, Q. Shi, A. van den Hengel, C. Shen, J. Gao, F. Hu, Z. Zhang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  3. Supervised discrete hashing
    \(\cdot\) F. Shen, C. Shen, W. Liu, H. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholarproject webpage

  4. Learning to rank in person re-identification with metric ensembles
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. The treasure beneath convolutional layers: cross convolutional layer pooling for image classification
    \(\cdot\) L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Deep convolutional neural fields for depth estimation from a single image
    \(\cdot\) F. Liu, C. Shen, G. Lin.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  7. Mid-level deep pattern mining
    \(\cdot\) Y. Li, L. Liu, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  8. Depth and surface normal estimation from monocular images using regression on deep features and hierarchical CRFs
    \(\cdot\) B. Li, C. Shen, Y. Dai, A. van den Hengel, M. He.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’15), 2015.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  9. Hyperspectral compressive sensing using manifold-structured sparsity prior
    \(\cdot\) L. Zhang, W. Wei, Y. Zhang, F. Li, C. Shen, Q. Shi.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’15), 2015.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  10. Deeply learning the messages in message passing inference
    \(\cdot\) G. Lin, C. Shen, I. Reid, A. van den Hengel.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’15), 2015.
    \(\cdot\) arXivpdfbibtexgoogle scholarsemantic scholar

  11. Sequence searching with deep-learnt depth for condition- and viewpoint-invariant route-based place recognition
    \(\cdot\) M. Milford, C. Shen, S. Lowry, N. Suenderhauf, S. Shirazi, G. Lin, F. Liu, E. Pepperell, C. Lerma, B. Upcroft, I. Reid.
    \(\cdot\) Proc. 6th International Workshop on Computer Vision in Vehicle Technology, in conjunction with IEEE Conference on Computer Vision and Pattern Recognition (CVVT’15), 2015.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

    1. Best paper award (Sponsored by NVIDIA).

2014

Journal

  1. Fast approximate \(l_\infty\) minimization: Speeding up robust regression
    \(\cdot\) F. Shen, C. Shen, R. Hill, A. van den Hengel, Z. Tang.
    \(\cdot\) Computational Statistics and Data Analysis (CSDA), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Multiple kernel learning in the primal for multi-modal Alzheimer's disease classification
    \(\cdot\) F. Liu, L. Zhou, C. Shen, J. Yin.
    \(\cdot\) IEEE Journal of Biomedical and Health Informatics (JBHI), 2014.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

    1. Online published at IEEE: 10 October 2013.

  3. Multiple kernel clustering based on centered kernel alignment
    \(\cdot\) Y. Lu, L. Wang, J. Lu, J. Yang, C. Shen.
    \(\cdot\) Pattern Recognition (PR), 2014.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Efficient semidefinite spectral clustering via Lagrange duality
    \(\cdot\) Y. Yan, C. Shen, H. Wang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  5. Large-margin learning of compact binary image encodings
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Characterness: An indicator of text in the wild
    \(\cdot\) Y. Li, W. Jia, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2014.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  7. Context-aware hypergraph construction for robust spectral clustering
    \(\cdot\) X. Li, W. Hu, C. Shen, A. Dick, Z. Zhang.
    \(\cdot\) IEEE Transactions on Knowledge and Data Engineering (TKDE), 2014.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  8. Asymmetric pruning for learning cascade detectors
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2014.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  9. Efficient dual approach to distance metric learning
    \(\cdot\) C. Shen, J. Kim, F. Liu, L. Wang, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  10. A scalable stage-wise approach to large-margin multi-class loss based boosting
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2014.
    \(\cdot\) arXivlinkpdfbibtexgoogle scholarsemantic scholar

  11. RandomBoost: Simplified multi-class boosting through randomization
    \(\cdot\) S. Paisitkriangkrai, C. Shen, Q. Shi, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2014.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  12. A hierarchical word-merging algorithm with class separability measure
    \(\cdot\) L. Wang, L. Zhou, C. Shen, L. Liu, H. Liu.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  13. StructBoost: Boosting methods for predicting structured output variables
    \(\cdot\) C. Shen, G. Lin, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014.
    \(\cdot\) arXivlinkpdfbibtexgoogle scholarsemantic scholar

Conference

  1. Fast supervised hashing with decision trees for high-dimensional data
    \(\cdot\) G. Lin, C. Shen, Q. Shi, A. van den Hengel, D. Suter.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’14), 2014.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  2. Strengthening the effectiveness of pedestrian detection with spatially pooled features
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’14), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  3. Optimizing ranking measures for compact binary code learning
    \(\cdot\) G. Lin, C. Shen, J. Wu.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’14), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  4. Encoding high dimensional local features by sparse coding based Fisher vectors
    \(\cdot\) L. Liu, C. Shen, L. Wang, A. van den Hengel, C. Wang.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’14), 2014.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

2013

Journal

  1. Training effective node classifiers for cascade classification
    \(\cdot\) C. Shen, P. Wang, S. Paisitkriangkrai, A. van den Hengel.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2013.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  2. Fully corrective boosting with arbitrary loss and regularization
    \(\cdot\) C. Shen, H. Li, A. van den Hengel.
    \(\cdot\) Neural Networks (NN), 2013.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  3. Approximate least trimmed sum of squares fitting and applications in image analysis
    \(\cdot\) F. Shen, C. Shen, A. van den Hengel, Z. Tang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2013.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  4. Visual tracking with spatio-temporal Dempster-Shafer information fusion
    \(\cdot\) X. Li, A. Dick, C. Shen, Z. Zhang, A. van den Hengel, H. Wang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2013.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  5. A survey of appearance models in visual object tracking
    \(\cdot\) X. Li, W. Hu, C. Shen, Z. Zhang, A. Dick, A. van den Hengel.
    \(\cdot\) ACM Transactions on Intelligent Systems and Technology (TIST), 2013.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Shape similarity analysis by self-tuning locally constrained mixed-diffusion
    \(\cdot\) L. Luo, C. Shen, C. Zhang, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Multimedia (TMM), 2013.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  7. Incremental learning of 3D-DCT compact representations for robust visual tracking
    \(\cdot\) X. Li, A. Dick, C. Shen, A. van den Hengel, H. Wang.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2013.
    \(\cdot\) arXivlinkpdfbibtexgoogle scholarsemantic scholarproject webpage

Conference

  1. Part-based visual tracking with online latent structural learning
    \(\cdot\) R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholarproject webpage

  2. Bilinear programming for human activity recognition with unknown MRF graphs
    \(\cdot\) Z. Wang, Q. Shi, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  3. A fast semidefinite approach to solving binary quadratic problems
    \(\cdot\) P. Wang, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation, 60 out of 1870 submissions.

  4. Inductive hashing on manifolds
    \(\cdot\) F. Shen, C. Shen, Q. Shi, A. van den Hengel, Z. Tang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  5. Learning compact binary codes for visual tracking
    \(\cdot\) X. Li, C. Shen, A. Dick, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’13), 2013.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  6. Dictionary learning and sparse coding on Grassmann manifolds: an extrinsic solution
    \(\cdot\) M. Harandi, C. Sanderson, C. Shen, B. Lovell.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  7. Efficient pedestrian detection by directly optimizing the partial area under the ROC curve
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
    \(\cdot\) arXivpdfbibtexgoogle scholarsemantic scholar

  8. A general two-step approach to learning-based hashing
    \(\cdot\) G. Lin, C. Shen, D. Suter, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  9. Contextual hypergraph modeling for salient object detection
    \(\cdot\) X. Li, Y. Li, C. Shen, A. Dick, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’13), 2013.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  10. Extended depth-of-field via focus stacking and graph cuts
    \(\cdot\) C. Zhang, J. Bastian, C. Shen, A. van den Hengel, T. Shen.
    \(\cdot\) Proc. IEEE Conference on Image Processing (ICIP’13), 2013.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Approximate constraint generation for efficient structured boosting
    \(\cdot\) G. Lin, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Image Processing (ICIP’13), 2013.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. Leveraging surrounding context for scene text detection
    \(\cdot\) Y. Li, C. Shen, W. Jia, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Image Processing (ICIP’13), 2013.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  13. Learning hash functions using column generation
    \(\cdot\) X. Li, G. Lin, C. Shen, A. van den Hengel, A. Dick.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’13), 2013.
    \(\cdot\) arXivpdfbibtexgoogle scholarsemantic scholarproject webpage

    1. Oral presentation.

2012

Journal

  1. Positive semidefinite metric learning using boosting-like algorithms
    \(\cdot\) C. Shen, J. Kim, L. Wang, A. van den Hengel.
    \(\cdot\) Journal of Machine Learning Research (JMLR), 2012.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholarproject webpage

  2. Fast and robust object detection using asymmetric totally-corrective boosting
    \(\cdot\) P. Wang, C. Shen, N. Barnes, H. Zheng.
    \(\cdot\) IEEE Transactions on Neural Networks and Learning Systems (TNN), 2012.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  3. UBoost: Boosting with the Universum
    \(\cdot\) C. Shen, P. Wang, F. Shen, H. Wang.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2012.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

Conference

  1. Fast training of effective multi-class boosting using coordinate descent optimization
    \(\cdot\) G. Lin, C. Shen, A. van den Hengel, D. Suter.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’12), 2012.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  2. Sharing features in multi-class boosting via group sparsity
    \(\cdot\) S. Paisitkriangkrai, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’12), 2012.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  3. Non-sparse linear representations for visual tracking with online reservoir metric learning
    \(\cdot\) X. Li, C. Shen, Q. Shi, A. Dick, A. van den Hengel.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’12), 2012.
    \(\cdot\) arXivpdfbibtexgoogle scholarsemantic scholar

  4. Robust tracking with weighted online structured learning
    \(\cdot\) R. Yao, Q. Shi, C. Shen, Y. Zhang, A. van den Hengel.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’12), 2012.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  5. Is margin preserved after random projection?
    \(\cdot\) Q. Shi, C. Shen, R. Hill, A. van den Hengel.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’12), 2012.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

    1. This work provides an analysis of margin distortion under random projections, the conditions under which margins are preserved, and presents bounds on the margin distortion.

Other

  1. Semidefinite programming (book chapter in: encyclopedia of computer vision, springer)
    \(\cdot\) C. Shen, A. van den Hengel.
    \(\cdot\) 2012.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

2011

Journal

  1. Efficiently learning a detection cascade with sparse eigenvectors
    \(\cdot\) C. Shen, S. Paisitkriangkrai, J. Zhang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2011.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  2. Incremental training of a detector using online sparse eigen-decomposition
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2011.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

Conference

  1. Efficiently learning a distance metric for large margin nearest neighbor classification
    \(\cdot\) K. Park, C. Shen, Z. Hao, J. Kim.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’11), 2011.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Is face recognition really a compressive sensing problem?
    \(\cdot\) Q. Shi, A. Eriksson, A. van den Hengel, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  3. A scalable dual approach to semidefinite metric learning
    \(\cdot\) C. Shen, J. Kim, L. Wang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  4. A direct formulation for totally-corrective multi-class boosting
    \(\cdot\) C. Shen, Z. Hao.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  5. A generalized probabilistic framework for compact codebook creation
    \(\cdot\) L. Liu, L. Wang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  6. Real-time visual tracking using compressive sensing
    \(\cdot\) H. Li, C. Shen, Q. Shi.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’11), 2011.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  7. Laplacian margin distribution boosting for learning from sparsely labeled data
    \(\cdot\) T. Wang, X. He, C. Shen, N. Barnes.
    \(\cdot\) Proc. International Conference on Digital Image Computing: Techniques and Applications (DICTA’11), 2011.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. On the optimality of sequential forward feature selection using class separability measure
    \(\cdot\) L. Wang, C. Shen, R. Hartley.
    \(\cdot\) Proc. International Conference on Digital Image Computing: Techniques and Applications (DICTA’11), 2011.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Graph mode-based contextual kernels for robust SVM tracking
    \(\cdot\) X. Li, A. Dick, H. Wang, C. Shen, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’11), 2011.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

2010

Journal

  1. Interactive color image segmentation with linear programming
    \(\cdot\) H. Li, C. Shen.
    \(\cdot\) Machine Vision and Applications (MVA), 2010.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  2. Generalized kernel-based visual tracking
    \(\cdot\) C. Shen, J. Kim, H. Wang.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2010.
    \(\cdot\) arXivlinkpdfbibtexgoogle scholarsemantic scholarproject webpage

  3. Feature selection with redundancy-constrained class separability
    \(\cdot\) L. Zhou, L. Wang, C. Shen.
    \(\cdot\) IEEE Transactions on Neural Networks (TNN), 2010.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  4. Boosting through optimization of margin distributions
    \(\cdot\) C. Shen, H. Li.
    \(\cdot\) IEEE Transactions on Neural Networks (TNN), 2010.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  5. Scalable large-margin Mahalanobis distance metric learning
    \(\cdot\) C. Shen, J. Kim, L. Wang.
    \(\cdot\) IEEE Transactions on Neural Networks (TNN), 2010.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  6. On the dual formulation of boosting algorithms
    \(\cdot\) C. Shen, H. Li.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2010.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

Conference

  1. Pyramid center-symmetric local binary, trinary patterns for effective pedestrian detection
    \(\cdot\) Y. Zheng, C. Shen, R. Hartley, X. Huang.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’10), 2010.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  2. Asymmetric totally-corrective boosting for real-time object detection
    \(\cdot\) P. Wang, C. Shen, N. Barnes, H. Zheng, Z. Ren.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

    1. Oral presentation.

  3. Face detection with effective feature extraction
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Totally-corrective multi-class boosting
    \(\cdot\) Z. Hao, C. Shen, N. Barnes, B. Wang.
    \(\cdot\) Proc. Asian Conference on Computer Vision (ACCV’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. Rapid face recognition using hashing
    \(\cdot\) Q. Shi, H. Li, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’10), 2010.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  6. Robust face recognition via accurate face alignment and sparse representation
    \(\cdot\) H. Li, P. Wang, C. Shen.
    \(\cdot\) Proc. International Conference on on Digital Image Computing: Techniques and Applications (DICTA’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. LACBoost and FisherBoost: optimally building cascade classifiers
    \(\cdot\) C. Shen, P. Wang, H. Li.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’10), 2010.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  8. Improved human detection and classification in thermal images
    \(\cdot\) W. Wang, J. Zhang, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Image Processing (ICIP’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. Training a multi-exit cascade with linear asymmetric classification for efficient object detection
    \(\cdot\) P. Wang, C. Shen, H. Zheng, Z. Ren.
    \(\cdot\) Proc. IEEE International Conference on Image Processing (ICIP’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. Hippocampal shape classification using redundancy constrained feature selection
    \(\cdot\) L. Zhou, L. Wang, C. Shen, N. Barnes.
    \(\cdot\) Proc. International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI’10), 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

Other

  1. Proceedings of international conference on digital image computing: techniques and applications
    \(\cdot\) J. Zhang, C. Shen, G. Geers, Q. Wu.
    \(\cdot\) Editors, IEEE, 2010.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

2009

Conference

  1. A variant of the trace quotient formulation for dimensionality reduction
    \(\cdot\) P. Wang, C. Shen, H. Zheng, Z. Ren.
    \(\cdot\) Proc. 9th Asian Conference on Computer Vision (ACCV’09), 2009.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. A scalable algorithm for learning a Mahalanobis distance metric
    \(\cdot\) J. Kim, C. Shen, L. Wang.
    \(\cdot\) Proc. 9th Asian Conference on Computer Vision (ACCV’09), 2009.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Efficiently training a better visual detector with sparse eigenvectors
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’09), 2009.
    \(\cdot\) arXivlinkbibtexgoogle scholarsemantic scholar

  4. A two-layer night-time vehicle detector
    \(\cdot\) W. Wang, C. Shen, J. Zhang, S. Paisitkriangkrai.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’09), 2009.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. Smooth approximation of \(l_\infty\)-norm for multi-view geometry
    \(\cdot\) Y. Dai, H. Li, M. He, C. Shen.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’09), 2009.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  6. Positive semidefinite metric learning with boosting
    \(\cdot\) C. Shen, J. Kim, L. Wang, A. van den Hengel.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’09), 2009.
    \(\cdot\) arXivpdfbibtexgoogle scholarsemantic scholarproject webpage

2008

Journal

  1. Performance evaluation of local features in human classification and detection
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) IET Computer Vision (IETCV), 2008.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

    1. Invited submission, special issue of DICTA2007.

  2. Supervised dimensionality reduction via sequential semidefinite programming
    \(\cdot\) C. Shen, H. Li, M. Brooks.
    \(\cdot\) Pattern Recognition (PR), 2008.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  3. Fast pedestrian detection using a cascade of boosted covariance features
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2008.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

Conference

  1. Self-calibrating cameras using semidefinite programming
    \(\cdot\) C. Shen, H. Li, M. Brooks.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’08), 2008.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  2. Multi-view human motion capture with an improved deformation skin model
    \(\cdot\) Y. Lu, L. Wang, R. Hartley, H. Li, C. Shen.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’08), 2008.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Boosting the minimum margin: LPBoost vs. AdaBoost
    \(\cdot\) H. Li, C. Shen.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’08), 2008.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Learning cascaded reduced-set SVMs using linear programming
    \(\cdot\) J. Kim, C. Shen, L. Wang.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’08), 2008.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. A fast algorithm for creating a compact and discriminative visual codebook
    \(\cdot\) L. Wang, L. Zhou, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’08), 2008.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  6. Face detection from few training examples
    \(\cdot\) C. Shen, S. Paisitkriangkrai, J. Zhang.
    \(\cdot\) Proc. IEEE International Conference on Image Processing (ICIP’08), 2008.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  7. PSDBoost: matrix-generation linear programming for positive semidefinite matrices learning
    \(\cdot\) C. Shen, A. Welsh, L. Wang.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’08), 2008.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

  8. Real-time pedestrian detection using a boosted multi-layer classifier
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) Proc. 8th IEEE International Workshop on Visual Surveillance, in conjunction with European Conference on Computer Vision (ECCVW’08), 2008.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

2007

Journal

  1. Fast global kernel density mode seeking: applications to localization and tracking
    \(\cdot\) C. Shen, M. Brooks, A. van den Hengel.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2007.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  2. Adaptive object tracking based on an effective appearance filter
    \(\cdot\) H. Wang, D. Suter, K. Schindler, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2007.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

    1. Featured article of September issue 2007.

Conference

  1. A convex programming approach to the trace quotient problem
    \(\cdot\) C. Shen, H. Li, M. Brooks.
    \(\cdot\) Proc. 8th Asian Conference on Computer Vision (ACCV’07), 2007.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  2. Kernel-based tracking from a probabilistic viewpoint
    \(\cdot\) Q. Nguyen, A. Robles-Kelly, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’07), 2007.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

  3. Feature extraction using sequential semidefinite programming
    \(\cdot\) C. Shen, H. Li, M. Brooks.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’07), 2007.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  4. An experimental evaluation of local features for pedestrian classification
    \(\cdot\) S. Paisitkriangkrai, C. Shen, J. Zhang.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’07), 2007.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

    1. Best Paper Award.

  5. Color image labelling using linear programming
    \(\cdot\) H. Li, C. Shen, Z. Wen.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’07), 2007.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  6. Object-respecting colour image segmentation: an LP approach
    \(\cdot\) H. Li, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Image Processing (ICIP’07), 2007.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

2006

Conference

  1. Classification-based likelihood functions for Bayesian tracking
    \(\cdot\) C. Shen, H. Li, M. Brooks.
    \(\cdot\) Proc. IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS’06), 2006.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  2. Enhanced kernel-based tracking for monochromatic and thermographic video
    \(\cdot\) Q. Nguyen, A. Robles-Kelly, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS’06), 2006.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  3. An LMI approach for reliable PTZ camera self-calibration
    \(\cdot\) H. Li, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Advanced Video and Signal based Surveillance (AVSS’06), 2006.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

2005

Conference

  1. Fast global kernel density mode seeking with application to localisation and tracking
    \(\cdot\) C. Shen, M. Brooks, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’05), 2005.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

    1. Oral presentation, 45 out of 1200 submissions.

  2. Visual tracking via efficient kernel discriminant subspace learning
    \(\cdot\) C. Shen, A. van den Hengel, M. Brooks.
    \(\cdot\) Proc. IEEE International Conference on Image Processing (ICIP’05), 2005.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  3. Augmented particle filtering for efficient visual tracking
    \(\cdot\) C. Shen, M. Brooks, A. van den Hengel.
    \(\cdot\) Proc. IEEE International Conference on Image Processing (ICIP’05), 2005.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  4. Adaptive over-relaxed mean shift
    \(\cdot\) C. Shen, M. Brooks.
    \(\cdot\) Proc. 8th International Symposium on Signal Processing and Its Applications (ISSPA’05), 2005.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

    1. Errata: in figure 3 square marker and circle marker should be swapped.

2004

Journal

  1. Active control of radiation from a piston set in a rigid sphere
    \(\cdot\) Z. Lin, J. Lu, C. Shen, X. Qiu, B. Xu.
    \(\cdot\) Journal of Acoustical Society of America (JASA), 2004.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

Conference

  1. Enhanced importance sampling: unscented auxiliary particle filtering for visual tracking
    \(\cdot\) C. Shen, A. van den Hengel, A. Dick, M. Brooks.
    \(\cdot\) Proc. Australian Joint Conference on Artificial Intelligence (AI’04), 2004.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

  2. 2D articulated tracking with dynamic Bayesian networks
    \(\cdot\) C. Shen, A. van den Hengel, A. Dick, M. Brooks.
    \(\cdot\) Proc. International Conference on Computer and Information Technology (CIT’04), 2004.
    \(\cdot\) linkbibtexgoogle scholarsemantic scholar

2003

Journal

  1. Lattice form adaptive infinite impulse response filtering algorithm for active noise control
    \(\cdot\) J. Lu, C. Shen, X. Qiu, B. Xu.
    \(\cdot\) Journal of Acoustical Society of America (JASA), 2003.
    \(\cdot\) linkpdfbibtexgoogle scholarsemantic scholar

Conference

  1. Probabilistic multiple cue integration for particle filter based tracking
    \(\cdot\) C. Shen, A. van den Hengel, A. Dick.
    \(\cdot\) Proc. International Conference on Digital Image Computing - Techniques and Applications (DICTA’03), 2003.
    \(\cdot\) pdfbibtexgoogle scholarsemantic scholar

    1. Nominated for Best Student Paper Award.