Publications (Full List)

Google scholar (102085 citations) , DBLP , arXiv .

Journal

1. Multi-modal primitive retrieval for compositional zero-shot learning
   \(\cdot\) C. Jing, H. Zhang, J. Lu, Y. Liu, H. Chen, X. Zhang, C. Shen.
   \(\cdot\) International Journal of Computer Vision (IJCV), 2026.
   \(\cdot\) bibtexsearch

2. Atlas of predicted protein complex structures across kingdoms
   \(\cdot\) D. Ma, X. Qi, C. Ye, J. Liang, S. Wen, Y. Li, K. Ding, Y. Hao, J. Fei, W. Mao, L. Li, Z. Lin, Y. Shen, H. Zhu, Y. Hu, R. Zhang, P. Ji, Y. Lu, B. Liu, H. Wang, Y. Chen, Z. Ma, P. Yang, X. Xu, J. Wu, Y. Zhu, Q. Zou, W. Zhu, K. Yao, S. Li, H. Xin, D. Ergu, J. Zeng, Z. Xiao, C. Shen.
   \(\cdot\) Nature Communications (Nat Commun), 2026.
   \(\cdot\) bibtexsearch

3. FreeCustom: training-free multi-concept customization for image and video generation
   \(\cdot\) C. Zhao, G. Ding, W. Wang, Z. Yang, Z. Liu, H. Chen, C. Shen.
   \(\cdot\) International Journal of Computer Vision (IJCV), 2025.
   \(\cdot\) bibtexsearch

4. 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.
   \(\cdot\) bibtexsearch

5. 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.
   \(\cdot\) bibtexsearch

6. 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.
   \(\cdot\) bibtexsearch

7. 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.
   \(\cdot\) bibtexsearch

8. 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.
   \(\cdot\) arXivbibtexsearch

9. 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.
   \(\cdot\) bibtexsearch

10. 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.
    \(\cdot\) bibtexsearch

11. 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.
    \(\cdot\) bibtexsearch

12. 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.
    \(\cdot\) bibtexsearch

13. 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.
    \(\cdot\) bibtexsearch

14. 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.
    \(\cdot\) bibtexsearch

15. Target before shooting: accurate anomaly detection and localization under one millisecond via cascade patch retrieval
    \(\cdot\) H. Li, J. Hu, B. Li, H. Chen, Y. Zheng, C. Shen.
    \(\cdot\) IEEE Transactions on Image Processing (TIP), 2024.
    \(\cdot\) bibtexsearch

16. 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.
    \(\cdot\) arXivbibtexsearch

17. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

18. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

19. 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.
    \(\cdot\) bibtexsearch

20. 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.
    \(\cdot\) arXivbibtexsearch

21. 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.
    \(\cdot\) bibtexsearch

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

23. 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.
    \(\cdot\) linkbibtexsearch

24. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

25. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

26. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

27. 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.
    \(\cdot\) arXivbibtexsearch

28. 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.
    \(\cdot\) bibtexsearch

29. 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.
    \(\cdot\) arXivbibtexsearch

30. 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.
    \(\cdot\) bibtexsearch

31. 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.
    \(\cdot\) bibtexsearch

32. 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.
    \(\cdot\) arXivbibtexsearch

33. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

34. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

35. 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.
    \(\cdot\) linkbibtexsearchproject webpage

36. 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.
    \(\cdot\) arXivbibtexsearch

37. 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.
    \(\cdot\) bibtexsearch

38. 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.
    \(\cdot\) bibtexsearch

39. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

40. 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.
    \(\cdot\) arXivbibtexsearch

41. 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.
    \(\cdot\) bibtexsearchproject webpage

42. 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.
    \(\cdot\) bibtexsearchproject webpage

43. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

44. 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.
    \(\cdot\) bibtexsearch

45. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

46. 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.
    \(\cdot\) bibtexsearch

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

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

49. 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.
    \(\cdot\) bibtexsearch

50. 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.
    \(\cdot\) arXivbibtexsearch

51. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

52. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

53. 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.
    \(\cdot\) arXivbibtexsearch

54. 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.
    \(\cdot\) arXivbibtexsearch

55. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

56. 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.
    \(\cdot\) bibtexsearch

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

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

59. 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.
    \(\cdot\) arXivbibtexsearch

60. 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.
    \(\cdot\) bibtexsearch

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

62. 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.
    \(\cdot\) arXivbibtexsearch

63. 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.
    \(\cdot\) bibtexsearch

64. 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.
    \(\cdot\) bibtexsearch

65. 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.
    \(\cdot\) bibtexsearch

66. 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.
    \(\cdot\) bibtexsearch

67. 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.
    \(\cdot\) arXivbibtexsearch

68. 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.
    \(\cdot\) arXivbibtexsearch

69. 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.
    \(\cdot\) bibtexsearch

70. 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.
    \(\cdot\) bibtexsearch

71. 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.
    \(\cdot\) bibtexsearch

72. 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.
    \(\cdot\) bibtexsearch

73. 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.
    \(\cdot\) bibtexsearch

74. 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.
    \(\cdot\) arXivbibtexsearch

75. 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.
    \(\cdot\) arXivlinkbibtexsearchproject webpage

76. 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.
    \(\cdot\) linkbibtexsearch

77. 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.
    \(\cdot\) arXivlinkbibtexsearchproject webpage

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

79. 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.
    \(\cdot\) arXivlinkbibtexsearchproject webpage

80. 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.
    \(\cdot\) arXivlinkbibtexsearch

81. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

82. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

83. 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.
    \(\cdot\) bibtexsearch

84. Heritage image annotation via collective knowledge
    \(\cdot\) J. Zhang, Q. Wu, J. Zhang, C. Shen, J. Lu, Q. Wu.
    \(\cdot\) Pattern Recognition (PR), 2019.
    \(\cdot\) bibtexsearch

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

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

87. 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.
    \(\cdot\) bibtexsearch

88. 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.
    \(\cdot\) bibtexsearch

89. 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.
    \(\cdot\) bibtexsearch

90. 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.
    \(\cdot\) bibtexsearch

91. 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.
    \(\cdot\) bibtexsearch

92. 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.
    \(\cdot\) bibtexsearch

93. 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.
    \(\cdot\) arXivbibtexsearch

94. 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.
    \(\cdot\) bibtexsearch

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

96. 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.
    \(\cdot\) arXivbibtexsearch

97. 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.
    \(\cdot\) linkbibtexsearchproject webpage

    1. Pytorch code is here.

98. 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.
    \(\cdot\) pdfbibtexsearch

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

100. 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.
     \(\cdot\) arXivbibtexsearch

101. 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.
     \(\cdot\) arXivbibtexsearch

102. 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.
     \(\cdot\) bibtexsearch

103. 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.
     \(\cdot\) bibtexsearch

104. 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.
     \(\cdot\) bibtexsearch

105. 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.
     \(\cdot\) bibtexsearch

106. 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.
     \(\cdot\) arXivbibtexsearch

107. 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.
     \(\cdot\) bibtexsearchproject webpage

108. 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.
     \(\cdot\) arXivbibtexsearch

109. 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.
     \(\cdot\) arXivbibtexsearch

110. 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.
     \(\cdot\) arXivbibtexsearch

111. 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.
     \(\cdot\) pdfbibtexsearch

112. 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.
     \(\cdot\) arXivbibtexsearch

113. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

114. 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.
     \(\cdot\) bibtexsearch

115. 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.
     \(\cdot\) arXivbibtexsearch

116. 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.
     \(\cdot\) arXivbibtexsearch

117. 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.
     \(\cdot\) bibtexsearch

118. 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.
     \(\cdot\) arXivbibtexsearch

119. 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.
     \(\cdot\) bibtexsearch

120. 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.
     \(\cdot\) arXivbibtexsearch

121. 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.
     \(\cdot\) arXivbibtexsearch

122. 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.
     \(\cdot\) arXivbibtexsearch

123. 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.
     \(\cdot\) arXivbibtexsearch

124. 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.
     \(\cdot\) arXivbibtexsearch

125. 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.
     \(\cdot\) arXivbibtexsearch

126. 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.
     \(\cdot\) arXivlinkbibtexsearch

127. 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.
     \(\cdot\) arXivbibtexsearch

128. 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.
     \(\cdot\) arXivbibtexsearch

129. 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.
     \(\cdot\) arXivbibtexsearch

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

131. 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.
     \(\cdot\) arXivlinkbibtexsearch

132. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

133. 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.
     \(\cdot\) arXivbibtexsearch

134. 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.
     \(\cdot\) linkbibtexsearch

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

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

137. 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.
     \(\cdot\) bibtexsearch

138. 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.
     \(\cdot\) linkbibtexsearch

139. 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.
     \(\cdot\) arXivbibtexsearch

140. 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.
     \(\cdot\) bibtexsearch

141. 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.
     \(\cdot\) linkbibtexsearch

142. 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.
     \(\cdot\) arXivlinkbibtexsearch

143. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

144. 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.
     \(\cdot\) arXivlinkbibtexsearch

145. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

146. 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.
     \(\cdot\) arXivbibtexsearch

147. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

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

149. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

150. 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.
     \(\cdot\) arXivbibtexsearch

151. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

152. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

153. 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.
     \(\cdot\) arXivbibtexsearch

154. 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.
     \(\cdot\) arXivlinkbibtexsearch

     1. Online published at IEEE: 10 October 2013.

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

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

157. 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.
     \(\cdot\) arXivbibtexsearch

158. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

159. 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.
     \(\cdot\) arXivlinkbibtexsearch

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

161. 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.
     \(\cdot\) arXivbibtexsearch

162. 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.
     \(\cdot\) arXivlinkbibtexsearch

163. 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.
     \(\cdot\) arXivlinkpdfbibtexsearch

164. 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.
     \(\cdot\) pdfbibtexsearch

165. 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.
     \(\cdot\) arXivlinkpdfbibtexsearch

166. 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.
     \(\cdot\) arXivlinkbibtexsearch

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

168. 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.
     \(\cdot\) linkpdfbibtexsearch

169. 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.
     \(\cdot\) pdfbibtexsearch

170. 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.
     \(\cdot\) arXivbibtexsearch

171. 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.
     \(\cdot\) pdfbibtexsearch

172. 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.
     \(\cdot\) arXivlinkpdfbibtexsearchproject webpage

173. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

174. 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.
     \(\cdot\) pdfbibtexsearch

175. 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.
     \(\cdot\) pdfbibtexsearch

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

177. 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.
     \(\cdot\) arXivlinkbibtexsearch

178. Interactive color image segmentation with linear programming
     \(\cdot\) H. Li, C. Shen.
     \(\cdot\) Machine Vision and Applications (MVA), 2010.
     \(\cdot\) linkpdfbibtexsearch

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

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

181. Boosting through optimization of margin distributions
     \(\cdot\) C. Shen, H. Li.
     \(\cdot\) IEEE Transactions on Neural Networks (TNN), 2010.
     \(\cdot\) arXivlinkbibtexsearch

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

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

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

     1. Invited submission, special issue of DICTA2007.

185. Supervised dimensionality reduction via sequential semidefinite programming
     \(\cdot\) C. Shen, H. Li, M. Brooks.
     \(\cdot\) Pattern Recognition (PR), 2008.
     \(\cdot\) linkpdfbibtexsearch

186. 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.
     \(\cdot\) linkpdfbibtexsearch

187. 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.
     \(\cdot\) linkpdfbibtexsearch

188. 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.
     \(\cdot\) linkpdfbibtexsearch

     1. Featured article of September issue 2007.

189. 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.
     \(\cdot\) linkpdfbibtexsearch

190. 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.
     \(\cdot\) linkpdfbibtexsearch

Conference

1. ODYSSEY: open-world quadrupeds exploration and manipulation for long-horizon tasks
   \(\cdot\) K. Wang, L. Lu, M. Liu, J. Jiang, Z. Li, B. Zhang, W. Zheng, X. Yu, H. Chen, C. Shen.
   \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’26), 2026.
   \(\cdot\) arXivbibtexsearch

   1. Oral presentation.

2. Exploring spatial intelligence from a generative perspective
   \(\cdot\) M. Zhu, S. Jiang, H. Zheng, Z. Luo, H. Zhong, A. Li, K. Wang, J. Rong, Y. Liu, H. Chen, T. Lin, C. Shen.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

3. Eliciting complex spatial reasoning in MLLMs through wide-baseline matching
   \(\cdot\) H. Zhong, M. Zhu, S. Zeng, A. Li, C. Chen, H. Geng, D. Shi, W. Ye, T. Lin, H. Chen, C. Shen.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

4. Unlocking the power of critical factors for 3D visual geometry estimation
   \(\cdot\) G. Xu, H. Geng, H. Zheng, S. Yin, Y. Sun, H. Chen, C. Shen.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

5. R\(^2\)-seg: training-free OOD medical tumor segmentation via anatomical reasoning and statistical rejection
   \(\cdot\) S. Shen, K. Liu, J. Xie, S. Gao, C. Shen, G. Liu, M. Crispin-Ortuzar, S. Gao.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

6. Preserving source video realism: high-fidelity face swapping for cinematic quality
   \(\cdot\) Z. Luo, Z. Du, Z. Zhu, H. Zhong, M. Zhu, W. Wang, Y. Xi, C. Jing, H. Chen, C. Shen.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

7. StaMo: unsupervised learning of generalizable robot motion from compact state representation
   \(\cdot\) M. Liu, J. Shu, H. Chen, Z. Li, C. Zhao, J. Yang, S. Gao, H. Chen, C. Shen.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

8. GeoMotion: rethinking motion segmentation via latent 4d geometry
   \(\cdot\) X. He, P. Lin, Y. Cui, D. Guo, C. Shen, X. Zhang.
   \(\cdot\) Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR’26), 2026.
   \(\cdot\) bibtexsearch

9. OmniWorld: a multi-domain and multi-modal dataset for 4d world modeling
   \(\cdot\) Y. Zhou, Y. Wang, J. Zhou, W. Chang, H. Guo, Z. Li, K. Ma, X. Li, Y. Wang, H. Zhu, M. Liu, D. Liu, J. Yang, Z. Fu, J. Chen, C. Shen, J. Pang, K. Zhang, T. He.
   \(\cdot\) Proc. International Conference on Learning Representations (ICLR’26), 2026.
   \(\cdot\) bibtexsearch

10. TINKER: diffusion's gift to 3d–multi-view consistent editing from sparse inputs without per-scene optimization
    \(\cdot\) C. Zhao, X. Li, T. Feng, Z. Zhao, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’26), 2026.
    \(\cdot\) bibtexsearch

11. \(\pi^3\): permutation-equivariant visual geometry learning
    \(\cdot\) Y. Wang, J. Zhou, H. Zhu, W. Chang, Y. Zhou, Z. Li, J. Chen, J. Pang, C. Shen, T. He.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’26), 2026.
    \(\cdot\) bibtexsearch

12. Time is a feature: exploiting temporal dynamics in diffusion language models
    \(\cdot\) W. Wang, B. Fang, C. Jing, Y. Shen, Y. Shen, Q. Wang, H. Ouyang, H. Chen, C. Shen.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’26), 2026.
    \(\cdot\) bibtexsearch

13. WinT3R: window-based streaming reconstruction with camera token pool
    \(\cdot\) Z. Li, J. Zhou, Y. Wang, H. Guo, W. Chang, Y. Zhou, H. Zhu, J. Chen, C. Shen, T. He.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’26), 2026.
    \(\cdot\) bibtexsearch

14. Uniform discrete diffusion with metric path for video generation
    \(\cdot\) H. Deng, T. Pan, F. Zhang, Y. Liu, Z. Luo, Y. Cui, W. Wang, C. Shen, S. Shan, Z. Zhang, X. Wang.
    \(\cdot\) Proc. International Conference on Learning Representations (ICLR’26), 2026.
    \(\cdot\) bibtexsearch

15. TG-LLaVA: text guided LLaVA via learnable latent embeddings
    \(\cdot\) D. Yan, P. Li, Y. Li, H. Chen, Q. Chen, W. Luo, W. Dong, Q. Yan, H. Zhang, C. Shen.
    \(\cdot\) Proc. AAAI Conference on Artificial Intelligence (AAAI’25), 2025.
    \(\cdot\) arXivbibtexsearch

16. 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.
    \(\cdot\) bibtexsearch

17. 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.
    \(\cdot\) bibtexsearch

18. 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.
    \(\cdot\) arXivbibtexsearch

19. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

20. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

21. 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.
    \(\cdot\) bibtexsearch

22. 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.
    \(\cdot\) bibtexsearch

23. 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.
    \(\cdot\) bibtexsearch

24. 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.
    \(\cdot\) bibtexsearch

25. 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.
    \(\cdot\) bibtexsearch

26. 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.
    \(\cdot\) bibtexsearch

27. 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.
    \(\cdot\) bibtexsearch

28. 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.
    \(\cdot\) bibtexsearch

    1. Spotlight presentation.

29. 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.
    \(\cdot\) bibtexsearch

30. 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.
    \(\cdot\) bibtexsearch

31. 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.
    \(\cdot\) bibtexsearch

32. 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.
    \(\cdot\) bibtexsearch

33. 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.
    \(\cdot\) bibtexsearch

    1. Spotlight presentation.

34. Generative video matting
    \(\cdot\) Y. Ge, K. Xie, G. Xu, M. Liu, L. Ke, L. Huang, H. Xue, H. Chen, C. Shen.
    \(\cdot\) Proc. ACM Special Interest Group on Computer Graphics and Interactive Techniques Conference (SIGGRAPH’25), 2025.
    \(\cdot\) bibtexsearch

35. 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.
    \(\cdot\) bibtexsearch

36. 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.
    \(\cdot\) bibtexsearch

37. 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.
    \(\cdot\) bibtexsearch

38. 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.
    \(\cdot\) bibtexsearch

39. 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.
    \(\cdot\) bibtexsearch

40. LoRAPrune: structured pruning meets low-rank parameter-efficient fine-tuning
    \(\cdot\) M. Zhang, H. Chen, C. Shen, Z. Yang, L. Ou, X. Yu, B. Zhuang.
    \(\cdot\) Proc. Findings of the Association for Computational Linguistics (EACL’24), 2024.
    \(\cdot\) bibtexsearch

41. StableLLaVA: enhanced visual instruction tuning with synthesized image-dialogue data
    \(\cdot\) Y. Li, C. Zhang, G. Yu, Z. Wang, B. Fu, G. Lin, C. Shen, L. Chen, Y. Wei.
    \(\cdot\) Proc. Findings of the Association for Computational Linguistics (EACL’24), 2024.
    \(\cdot\) bibtexsearch

42. 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.
    \(\cdot\) bibtexsearchproject webpage

43. 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.
    \(\cdot\) bibtexsearchproject webpage

44. 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.
    \(\cdot\) arXivlinkbibtexsearchproject webpage

45. 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.
    \(\cdot\) arXivreviewsbibtexsearch

    1. Spotlight presentation.

46. 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.
    \(\cdot\) arXivlinkbibtexsearch

47. 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.
    \(\cdot\) bibtexsearch

48. 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.
    \(\cdot\) bibtexsearch

49. 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.
    \(\cdot\) bibtexsearch

50. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

51. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

52. 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.
    \(\cdot\) bibtexsearch

53. 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.
    \(\cdot\) bibtexsearch

54. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

55. 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.
    \(\cdot\) bibtexsearch

56. 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.
    \(\cdot\) bibtexsearch

57. 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.
    \(\cdot\) arXivbibtexsearch

58. 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.
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59. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

60. 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.
    \(\cdot\) arXivbibtexsearch

61. 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.
    \(\cdot\) bibtexsearch

62. 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.
    \(\cdot\) arXivbibtexsearch

63. 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.
    \(\cdot\) arXivbibtexsearch

64. 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.
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    1. Oral presentation.

65. 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.
    \(\cdot\) arXivbibtexsearch

66. 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.
    \(\cdot\) bibtexsearchproject webpage

67. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

68. 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.
    \(\cdot\) arXivbibtexsearch

69. 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.
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70. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

71. 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.
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72. 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.
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73. 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.
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74. 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.
    \(\cdot\) arXivbibtexsearch

75. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

76. 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.
    \(\cdot\) arXivbibtexsearch

77. 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.
    \(\cdot\) bibtexsearchproject webpage

    1. Oral presentation.

78. 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.
    \(\cdot\) arXivbibtexsearch

79. 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.
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80. 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.
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81. 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.
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82. 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.
    \(\cdot\) bibtexsearch

83. 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.
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84. 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.
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85. 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.
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86. 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.
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87. 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.
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88. 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.
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89. Deep reasoning network for few-shot semantic segmentation
    \(\cdot\) Y. Zhuge, C. Shen.
    \(\cdot\) Proc. ACM International Conference on Multimedia (ACMMM’21), 2021.
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90. 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.
    \(\cdot\) arXivbibtexsearch

91. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

92. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

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

93. 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.
    \(\cdot\) arXivbibtexsearch

    1. Oral presentation.

94. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

    1. Oral presentation.

95. 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.
    \(\cdot\) arXivbibtexsearchproject webpage

96. 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.
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97. 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.
    \(\cdot\) bibtexsearch

98. 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.
    \(\cdot\) bibtexsearchproject webpage

99. 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.
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100. 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.
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101. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

102. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

103. 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.
     \(\cdot\) arXivbibtexsearch

104. 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.
     \(\cdot\) arXivbibtexsearch

     1. Oral presentation.

105. 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.
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106. A simple baseline for semi-supervised semantic segmentation with strong data augmentation
     \(\cdot\) J. Yuan, Y. Liu, C. Shen, Z. Wang, H. Li.
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107. 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.
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108. Occluded person re-identification with single-scale global representations
     \(\cdot\) C. Yan, G. Pang, J. Jiao, X. Bai, X. Feng, C. Shen.
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109. Channel-wise knowledge distillation for dense prediction
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110. FATNN: fast and accurate ternary neural networks
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111. FastFlowNet: a lightweight network for fast optical flow estimation
     \(\cdot\) L. Kong, C. Shen, J. Yang.
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112. Toward deep supervised anomaly detection: reinforcement learning from partially labeled anomaly data
     \(\cdot\) G. Pang, A. van den Hengel, C. Shen, L. Cao.
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113. CoTr: efficient 3D medical image segmentation by bridging CNN and transformer
     \(\cdot\) Y. Xie, J. Zhang, C. Shen, Y. Xia.
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114. Dynamic neural representational decoders for high-resolution semantic segmentation
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115. 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.
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116. Task-aware monocular depth estimation for 3D object detection
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117. 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.
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118. Training quantized neural networks with a full-precision auxiliary module
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119. Mask encoding for single shot instance segmentation
     \(\cdot\) R. Zhang, Z. Tian, C. Shen, M. You, Y. Yan.
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120. Memory-efficient hierarchical neural architecture search for image denoising
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121. DeepEMD: few-shot image classification with differentiable earth mover's distance and structured classifiers
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122. Context prior for scene segmentation
     \(\cdot\) C. Yu, J. Wang, C. Gao, G. Yu, C. Shen, N. Sang.
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123. PolarMask: single shot instance segmentation with polar representation
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124. On the general value of evidence, and bilingual scene-text visual question answering
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125. NAS-FCOS: fast neural architecture search for object detection
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126. REVERIE: remote embodied visual referring expression in real indoor environments
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127. Self-trained deep ordinal regression for end-to-end video anomaly detection
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128. ABCNet: arbitrarily-shaped scene text spotting with adaptive Bezier-curve network in real time
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129. BlendMask: top-down meets bottom-up for instance segmentation
     \(\cdot\) H. Chen, K. Sun, Z. Tian, C. Shen, Y. Huang, Y. Yan.
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130. Representative graph neural network
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131. Segmenting transparent objects in the wild
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132. SOLO: segmenting objects by locations
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133. Scene text image super-resolution in the wild
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134. AE TextSpotter: learning visual and linguistic representation for ambiguous text spotting
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135. Soft expert reward learning for vision-and-language navigation
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136. Conditional convolutions for instance segmentation
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137. Efficient semantic video segmentation with per-frame inference
     \(\cdot\) Y. Liu, C. Shen, C. Yu, J. Wang.
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138. Weighing counts: sequential crowd counting by reinforcement learning
     \(\cdot\) L. Liu, H. Lu, H. Zou, H. Xiong, Z. Cao, C. Shen.
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139. Instance-aware embedding for point cloud instance segmentation
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140. Learning and memorizing representative prototypes for 3D point cloud semantic and instance segmentation
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141. Unsupervised representation learning by predicting random distances
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142. Pairwise relation learning for semi-supervised gland segmentation
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143. SOLOv2: dynamic and fast instance segmentation
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144. Show, attend and read: a simple and strong baseline for irregular text recognition
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145. Deep hashing by discriminating hard examples
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146. Structured binary neural networks for accurate image classification and semantic segmentation
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147. Mind your neighbours: image annotation with metadata neighbourhood graph co-attention networks
     \(\cdot\) J. Zhang, Q. Wu, J. Zhang, C. Shen, J. Lu.
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148. CANet: class-agnostic segmentation networks with iterative refinement and attentive few-shot learning
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149. 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.
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150. Associatively segmenting instances and semantics in point clouds
     \(\cdot\) X. Wang, S. Liu, X. Shen, C. Shen, J. Jia.
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151. 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.
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152. Decoders matter for semantic segmentation: data-dependent decoding enables flexible feature aggregation
     \(\cdot\) Z. Tian, T. He, C. Shen, Y. Yan.
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153. Fast neural architecture search of compact semantic segmentation models via auxiliary cells
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154. Visual question answering as reading comprehension
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155. Knowledge adaptation for efficient semantic segmentation
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156. Self-training with progressive augmentation for unsupervised cross-domain person re-identification
     \(\cdot\) X. Zhang, J. Cao, C. Shen, M. You.
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157. Exploiting temporal consistency for real-time video depth estimation
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158. Enforcing geometric constraints of virtual normal for depth prediction
     \(\cdot\) W. Yin, Y. Liu, C. Shen, Y. Yan.
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159. 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.
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160. 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.
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161. FCOS: fully convolutional one-stage object detection
     \(\cdot\) Z. Tian, C. Shen, H. Chen, T. He.
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162. Indices matter: learning to index for deep image matting
     \(\cdot\) H. Lu, Y. Dai, C. Shen, S. Xu.
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163. Real-time joint semantic segmentation and depth estimation using asymmetric annotations
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164. Light-weight hybrid convolutional network for liver tumor segmentation
     \(\cdot\) J. Zhang, Y. Xie, P. Zhang, H. Chen, Y. Xia, C. Shen.
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165. Deep anomaly detection with deviation networks
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166. Deep segmentation-emendation model for gland instance segmentation
     \(\cdot\) Y. Xie, H. Lu, J. Zhang, C. Shen, Y. Xia.
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167. Multi-marginal wasserstein GAN
     \(\cdot\) J. Cao, L. Mo, Y. Zhang, K. Jia, C. Shen, M. Tan.
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168. 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.
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169. HCVRD: a benchmark for large-scale human-centered visual relationship detection
     \(\cdot\) B. Zhuang, Q. Wu, C. Shen, I. Reid, A. van den Hengel.
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170. 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.
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171. Coarse-to-fine: a RNN-based hierarchical attention model for vehicle re-identification
     \(\cdot\) X. Wei, C. Zhang, L. Liu, C. Shen, J. Wu.
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172. Deep attention-based classification network for robust depth prediction
     \(\cdot\) R. Li, K. Xian, C. Shen, Z. Cao, H. Lu, L. Hang.
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173. Light-weight refinenet for real-time semantic segmentation
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174. A hybrid probabilistic model for camera relocalization
     \(\cdot\) M. Cai, C. Shen, I. Reid.
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175. Towards effective low-bitwidth convolutional neural networks
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176. Parallel attention: a unified framework for visual object discovery through dialogs and queries
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177. Monocular relative depth perception with web stereo data supervision
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178. Are you talking to me? reasoned visual dialog generation through adversarial learning
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179. Repulsion loss: detecting pedestrians in a crowd
     \(\cdot\) X. Wang, T. Xiao, Y. Jiang, S. Shao, J. Sun, C. Shen.
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180. 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.
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181. Bootstrapping the performance of webly supervised semantic segmentation
     \(\cdot\) T. Shen, G. Lin, C. Shen, I. Reid.
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182. Visual question answering with memory-augmented networks
     \(\cdot\) C. Ma, C. Shen, A. Dick, Q. Wu, P. Wang, A. van den Hengel, I. Reid.
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183. An end-to-end textspotter with explicit alignment and attention
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184. FSRNet: end-to-end learning face super-resolution with facial priors
     \(\cdot\) Y. Chen, Y. Tai, X. Liu, C. Shen, J. Yang.
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185. Goal-oriented visual question generation via intermediate rewards
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186. Learning to predict crisp boundaries
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187. Learning deep representations using convolutional auto-encoders with symmetric skip connections
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188. Adversarial learning with local coordinate coding
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189. Salient object detection by lossless feature reflection
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190. Auxiliary tasks to improve trip hazard affordance detection
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191. Weakly supervised semantic segmentation based on co-segmentation
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192. Visually aligned word embeddings for improving zero-shot learning
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193. Attend in groups: a weakly-supervised deep learning framework for learning from web data
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194. Multi-attention network for one shot learning
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195. The VQA-machine: learning how to use existing vision algorithms to answer new questions
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196. RefineNet: multi-path refinement networks for high-resolution semantic segmentation
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     1. Light-weight RefineNet with Pytorch code.

197. Sequential person recognition in photo albums with a recurrent network
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198. From motion blur to motion flow: a deep learning solution for removing heterogeneous motion blur
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199. Towards context-aware interaction recognition
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200. When unsupervised domain adaptation meets tensor representations
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201. Semi-global weighted least squares in image filtering
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202. Towards end-to-end text spotting with convolutional recurrent neural networks
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203. Adversarial PoseNet: a structure-aware convolutional network for human pose estimation
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     \(\cdot\) Proc. IEEE International Conference on Computer Vision (ICCV’17), 2017.
     \(\cdot\) arXivbibtexsearch

204. 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.
     \(\cdot\) arXivbibtexsearch

205. 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.
     \(\cdot\) arXivbibtexsearch

206. 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.
     \(\cdot\) arXivbibtexsearch

207. 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.
     \(\cdot\) arXivbibtexsearch

208. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

209. 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.
     \(\cdot\) arXivbibtexsearch

210. 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.
     \(\cdot\) arXivbibtexsearch

211. 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.
     \(\cdot\) arXivbibtexsearch

212. 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.
     \(\cdot\) arXivbibtexsearch

213. 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.
     \(\cdot\) arXivbibtexsearch

214. 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.
     \(\cdot\) bibtexsearch

215. 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.
     \(\cdot\) arXivbibtexsearch

216. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

     1. Others have implemented our paper.

217. 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.
     \(\cdot\) arXivbibtexsearch

218. 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.
     \(\cdot\) pdfbibtexsearch

219. 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.
     \(\cdot\) pdfbibtexsearchproject webpage

220. 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.
     \(\cdot\) arXivbibtexsearch

221. 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.
     \(\cdot\) arXivbibtexsearch

222. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

223. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

224. 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.
     \(\cdot\) pdfbibtexsearch

225. 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.
     \(\cdot\) pdfbibtexsearch

226. 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.
     \(\cdot\) arXivpdfbibtexsearch

227. 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.
     \(\cdot\) pdfbibtexsearch

     1. Best paper award (Sponsored by NVIDIA).

228. 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.
     \(\cdot\) arXivlinkbibtexsearchproject webpage

229. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

230. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

231. 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.
     \(\cdot\) arXivbibtexsearch

232. 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.
     \(\cdot\) linkpdfbibtexsearchproject webpage

233. 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.
     \(\cdot\) linkpdfbibtexsearch

234. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

     1. Oral presentation, 60 out of 1870 submissions.

235. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

236. 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.
     \(\cdot\) linkpdfbibtexsearch

237. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

238. 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.
     \(\cdot\) arXivpdfbibtexsearch

239. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

240. 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.
     \(\cdot\) arXivbibtexsearchproject webpage

241. 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.
     \(\cdot\) bibtexsearch

242. 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.
     \(\cdot\) bibtexsearch

243. 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.
     \(\cdot\) bibtexsearch

244. 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.
     \(\cdot\) arXivpdfbibtexsearchproject webpage

     1. Oral presentation.

245. 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.
     \(\cdot\) arXivbibtexsearch

246. 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.
     \(\cdot\) pdfbibtexsearch

247. 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.
     \(\cdot\) arXivpdfbibtexsearch

248. 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.
     \(\cdot\) pdfbibtexsearch

249. 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.
     \(\cdot\) arXivlinkbibtexsearch

     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.

250. 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.
     \(\cdot\) bibtexsearch

251. 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.
     \(\cdot\) pdfbibtexsearch

252. 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.
     \(\cdot\) pdfbibtexsearch

253. 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.
     \(\cdot\) pdfbibtexsearch

254. 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.
     \(\cdot\) pdfbibtexsearch

255. 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.
     \(\cdot\) pdfbibtexsearch

256. 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.
     \(\cdot\) bibtexsearch

257. 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.
     \(\cdot\) bibtexsearch

258. 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.
     \(\cdot\) pdfbibtexsearch

259. 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.
     \(\cdot\) pdfbibtexsearch

260. 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.
     \(\cdot\) bibtexsearch

     1. Oral presentation.

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

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

263. 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.
     \(\cdot\) pdfbibtexsearch

264. 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.
     \(\cdot\) bibtexsearch

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

266. 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.
     \(\cdot\) bibtexsearch

267. 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.
     \(\cdot\) bibtexsearch

268. 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.
     \(\cdot\) bibtexsearch

269. 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.
     \(\cdot\) bibtexsearch

270. 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.
     \(\cdot\) bibtexsearch

271. 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.
     \(\cdot\) arXivlinkbibtexsearch

272. 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.
     \(\cdot\) bibtexsearch

273. 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.
     \(\cdot\) bibtexsearch

274. 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.
     \(\cdot\) arXivpdfbibtexsearchproject webpage

275. 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.
     \(\cdot\) linkbibtexsearch

276. 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.
     \(\cdot\) bibtexsearch

277. 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.
     \(\cdot\) bibtexsearch

278. 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.
     \(\cdot\) bibtexsearch

279. 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.
     \(\cdot\) linkpdfbibtexsearch

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

281. 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.
     \(\cdot\) pdfbibtexsearch

282. 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.
     \(\cdot\) bibtexsearch

283. 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.
     \(\cdot\) linkbibtexsearch

284. 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.
     \(\cdot\) linkpdfbibtexsearch

285. 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.
     \(\cdot\) linkbibtexsearch

286. 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.
     \(\cdot\) linkbibtexsearch

     1. Best Paper Award.

287. 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.
     \(\cdot\) linkbibtexsearch

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

289. 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.
     \(\cdot\) linkbibtexsearch

290. 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.
     \(\cdot\) linkbibtexsearch

291. 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.
     \(\cdot\) linkbibtexsearch

292. 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.
     \(\cdot\) linkpdfbibtexsearch

     1. Oral presentation, 45 out of 1200 submissions.

293. 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.
     \(\cdot\) linkbibtexsearch

294. 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.
     \(\cdot\) linkbibtexsearch

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

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

296. 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.
     \(\cdot\) linkbibtexsearch

297. 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.
     \(\cdot\) linkbibtexsearch

298. 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.
     \(\cdot\) pdfbibtexsearch

     1. Nominated for Best Student Paper Award.

Other

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

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