Selected Publications

Google scholar (97149 citations) , DBLP , arXiv .

Journal: 76

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI): 47

International Journal of Computer Vision (IJCV): 29


  1. Paragraph-to-image generation with information-enriched diffusion model
    \(\cdot\) W. Wu, Z. Li, Y. He, M. Shou, C. Shen, L. Cheng, Y. Li, T. Gao, Z. Di.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. Segment anything in context with vision foundation models
    \(\cdot\) Y. Liu, M. Zhu, H. Chen, X. Wang, B. Feng, H. Wang, S. Li, R. Vemulapalli, C. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. PonderV2: pave the way for 3D foundation model with a universal pre-training paradigm
    \(\cdot\) H. Zhu, H. Yang, X. Wu, D. Huang, S. Zhang, X. He, H. Zhao, C. Shen, Y. Qiao, T. He, W. Ouyang.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  4. Leaning dual-stream conditional concepts in compositional zero-shot learning
    \(\cdot\) Q. Wang, L. Liu, C. Jing, P. Wang, Y. Zhang, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  5. VimTS: a unified video and image text spotter for enhancing the cross-domain generalization
    \(\cdot\) Y. Liu, M. Huang, H. Yan, L. Deng, W. Wu, H. Lu, C. Shen, L. Jin, X. Bai.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  6. Diffusion models are efficient data generators for human mesh recovery
    \(\cdot\) Y. Ge, W. Wang, Y. Chen, F. Wang, L. Yang, H. Chen, C. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. Scaling up multi-domain semantic segmentation with sentence embeddings
    \(\cdot\) W. Yin, Y. Liu, C. Shen, B. Sun, A. van den Hengel.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. 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

  9. 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

  10. AutoStory: generating diverse storytelling images with minimal human effort
    \(\cdot\) W. Wang, C. Zhao, H. Chen, Z. Chen, K. Zheng, C. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. Masked channel modeling for bootstrapping visual pre-training
    \(\cdot\) Y. Liu, X. Wang, M. Zhu, Y. Cao, T. Huang, C. Shen.
    \(\cdot\) International Journal of Computer Vision (IJCV), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. Self-supervised 3d scene flow estimation and motion prediction using local rigidity prior
    \(\cdot\) R. Li, C. Zhang, Z. Wang, C. Shen, G. Lin.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  13. Metric3D v2: a versatile monocular geometric foundation model for zero-shot metric depth and surface normal estimation
    \(\cdot\) M. Hu, W. Yin, C. Zhang, Z. Cai, X. Long, H. Chen, K. Wang, G. Yu, C. Shen, S. Shen.
    \(\cdot\) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2024.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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

  28. 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

  29. 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

  30. 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

  31. 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

  32. 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

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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

  40. 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

  41. 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

  42. 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

  43. 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

  44. 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

  45. 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

  46. 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

  47. 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

  48. 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

  49. 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

  50. 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

  51. 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.

  52. 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

  53. 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

  54. 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

  55. 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

  56. 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

  57. 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

  58. 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

  59. 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

  60. 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

  61. 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

  62. 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

  63. 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

  64. 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

  65. 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

  66. 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

  67. 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

  68. 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

  69. 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

  70. 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

  71. 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

  72. 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

  73. 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

  74. 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

  75. 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

  76. 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: 202

Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 95

Proc. IEEE International Conference on Computer Vision (ICCV): 40

Proc. European Conference on Computer Vision (ECCV): 26

Proc. International Conference on Machine Learning (ICML): 7

Proc. International Conference on Learning Represenations (ICLR): 11

Proc. Advances in Neural Information Processing Systems (NeurIPS): 23


  1. SegAgent: exploring pixel understanding capabilities in MLLMs by imitating human annotator trajectories
    \(\cdot\) M. Zhu, Y. Tian, H. Chen, C. Zhou, Q. Guo, Y. Liu, M. Yang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  2. MovieBench: a hierarchical movie level dataset for long video generation
    \(\cdot\) W. Wu, M. Liu, Z. Zhu, F. Haoen, X. Xia, W. Wang, K. Lin, C. Shen, M. Shou.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  3. Fine-grained abnormality prompt learning for zero-shot anomaly detection
    \(\cdot\) J. Zhu, Y. Ong, C. Shen, G. Pang.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’25), 2025.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholar

  4. Aether: geometric-aware unified world modeling
    \(\cdot\) H. Zhu, Y. Wang, J. Zhou, W. Chang, Y. Zhou, Z. Li, J. Chen, C. Shen, J. Pang, T. He.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’25), 2025.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  5. Pomato: marrying pointmap matching with temporal motions for dynamic 3D reconstruction
    \(\cdot\) S. Zhang, Y. Ge, J. Tian, G. Xu, H. Chen, C. Lv, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’25), 2025.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  6. Unified open-world segmentation with multi-modal prompts
    \(\cdot\) Y. Liu, Y. Yin, C. Jin, M. Zhu, H. Chen, Y. Xi, B. Feng, H. Wang, S. Li, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  7. SurfaceSplat: connecting surface reconstruction and gaussian splatting
    \(\cdot\) Z. Gao, J. Bian, G. Lin, H. Chen, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  8. SMSTracker: tri-path score mask sigma fusion for multi-modal tracking
    \(\cdot\) S. Chan, Z. Li, X. Zhang, W. Li, S. Lu, C. Shen.
    \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  9. MovieDreamer: hierarchical generation for coherent long visual sequences
    \(\cdot\) C. Zhao, M. Liu, W. Wang, W. Chen, F. Wang, H. Chen, B. Zhang, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  10. Depth any video with scalable synthetic data
    \(\cdot\) H. Yang, D. Huang, W. Yin, C. Shen, H. Liu, X. He, B. Lin, W. Ouyang, T. Hi.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  11. What matters when repurposing diffusion models for general dense perception tasks?
    \(\cdot\) G. Xu, Y. Ge, M. Liu, C. Fan, K. Xie, Z. Zhao, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  12. Framer: interactive frame interpolation
    \(\cdot\) W. Wang, Q. Wang, K. Zheng, H. Ouyang, Z. Chen, B. Gong, H. Chen, Y. Shen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  13. Boltzmann-aligned inverse folding model as a predictor of mutational effects on protein-protein interactions
    \(\cdot\) X. Jiao, W. Mao, W. Jin, P. Yang, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

    1. Spotlight presentation.

  14. PerturboLLaVA: reducing multimodal hallucinations with perturbative visual training
    \(\cdot\) C. Chen, M. Liu, C. Jing, Y. Zhou, F. Rao, H. Chen, B. Zhang, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  15. Revisiting convolution architecture in the realm of DNA foundation models
    \(\cdot\) Y. Bo, W. Mao, Y. Shao, W. Bai, P. Ye, X. Ma, J. Zhao, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  16. Physics aware neural networks for unsupervised binding energy prediction
    \(\cdot\) K. Liu, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  17. Omni-R1: reinforcement learning for omnimodal reasoning via two-system collaboration
    \(\cdot\) H. Zhong, M. Zhu, Z. Du, Z. Huang, C. Zhao, M. Liu, W. Wang, H. Chen, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  18. Diception: a generalist diffusion model for visual perceptual tasks
    \(\cdot\) C. Zhao, Y. Sun, M. Liu, H. Zheng, M. Zhu, Z. Zhao, H. Chen, T. He, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’25), 2025.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

    1. Spotlight presentation.

  19. Traffic scene parsing through the tsp6k dataset
    \(\cdot\) P. Jiang, Y. Yang, Y. Cao, Q. Hou, M. Cheng, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  20. DiverGen: improving instance segmentation by learning wider data distribution with more diverse generative data
    \(\cdot\) C. Fan, M. Zhu, H. Chen, Y. Liu, W. Wu, H. Zhang, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  21. FreeCustom: tuning-free customized image generation for multi-concept composition
    \(\cdot\) G. Ding, C. Zhao, W. Wang, Z. Yang, Z. Liu, H. Chen, C. Shen.
    \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  22. VisionLLaMA: a unified llama backbone for vision tasks
    \(\cdot\) X. Chu, J. Su, B. Zhang, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  23. FreeCompose: generic zero-shot image composition with diffusion prior
    \(\cdot\) Z. Chen, W. Wang, Z. Yang, Z. Yuan, H. Chen, C. Shen.
    \(\cdot\) Proc. European Conference on Computer Vision (ECCV’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholarproject webpage

  24. 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

  25. 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.
    \(\cdot\) arXivreviewsbibtexgoogle scholarsemantic scholar

    1. Spotlight presentation.

  26. 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

  27. Generative active learning for long-tailed instance segmentation
    \(\cdot\) M. Zhu, C. Fan, H. Chen, Y. Liu, W. Mao, X. Xu, C. Shen.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  28. Floating anchor diffusion model for multi-motif scaffolding
    \(\cdot\) K. Liu, S. Shen, W. Mao, X. Jiao, Z. Sun, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  29. On the trajectory regularity of ODE-based diffusion sampling
    \(\cdot\) D. Chen, Z. Zhou, C. Wang, C. Shen, S. Lyu.
    \(\cdot\) Proc. International Conference on Machine Learning (ICML’24), 2024.
    \(\cdot\) bibtexgoogle scholarsemantic scholar

  30. Unleashing the potential of the diffusion model in few-shot semantic segmentation
    \(\cdot\) M. Zhu, Y. Liu, Z. Luo, C. Jing, H. Chen, G. Xu, X. Wang, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’24), 2024.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  31. A simple image segmentation framework via in-context examples
    \(\cdot\) Y. Liu, C. Jing, H. Li, M. Zhu, H. Chen, X. Wang, C. Shen.
    \(\cdot\) Proc. Advances in Neural Information Processing Systems (NeurIPS’24), 2024.
    \(\cdot\) arXivbibtexgoogle scholarsemantic scholarproject webpage

  32. 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

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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

  40. 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

  41. 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

  42. 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.

  43. 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

  44. 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

  45. 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

  46. 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

  47. 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

  48. 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

  49. 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

  50. 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

  51. 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

  52. 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

  53. 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.

  54. 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

  55. 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

  56. 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

  57. 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

  58. 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

  59. 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

  60. 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

  61. 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

  62. 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

  63. 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

  64. 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.

  65. 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.

  66. 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.

  67. 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

  68. 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

  69. 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

  70. 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

  71. 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

  72. 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

  73. 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

  74. 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

  75. 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

  76. 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.

  77. 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

  78. 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

  79. 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

  80. 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.

  81. 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

  82. 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

  83. 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

  84. 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

  85. 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.

  86. 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

  87. 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

  88. 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.

  89. 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

  90. 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.

  91. 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

  92. 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

  93. 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.

  94. 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

  95. 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.

  96. 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.

  97. 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

  98. 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

  99. 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

  100. 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

  101. 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

  102. 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

  103. 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.

  104. 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

  105. 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

  106. 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

  107. 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

  108. 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

  109. 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

  110. 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

  111. 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

  112. 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

  113. 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

  114. 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

  115. 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

  116. 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

  117. 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

  118. 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

  119. 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

  120. 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

  121. 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

  122. 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

  123. 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

  124. 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

  125. 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

  126. 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

  127. 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

  128. 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

  129. 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

  130. 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

  131. 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

  132. 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.

  133. 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

  134. 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

  135. 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

  136. 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

  137. 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

  138. 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

  139. 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

  140. 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

  141. 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

  142. 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

  143. 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

  144. 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.

  145. 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

  146. 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

  147. 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

  148. 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

  149. 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

  150. 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

  151. 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

  152. 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

  153. 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

  154. 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

  155. 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

  156. 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

  157. 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

  158. 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

  159. 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

  160. 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.

  161. 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

  162. 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

  163. 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

  164. 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

  165. 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

  166. 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

  167. 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

  168. 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

  169. 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

  170. 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

  171. 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

  172. 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

  173. 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

  174. 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

  175. 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

  176. 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

  177. 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.

  178. 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

  179. 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

  180. 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

  181. 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

  182. 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

  183. 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

  184. 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.

  185. 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

  186. 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

  187. 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

  188. 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.

  189. 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

  190. 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

  191. 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

  192. 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

  193. 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

  194. 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

  195. 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

  196. 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

  197. 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

  198. 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

  199. 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

  200. 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

  201. 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

  202. 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.