Selected Publications

Google scholar (15807 citations) , DBLP , arXiv .

Journal

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI): 21

International Journal of Computer Vision (IJCV): 8

Journal of Machine Learning Research (JMLR): 1


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

  2. 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

  3. 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

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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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), 2019.
    cdot arXivbibtexsearch

  12. 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 bibtexsearchproject webpage

    1. Pytorch code is here.

  13. 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

  14. 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

  15. 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

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

  17. 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

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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

  28. 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

  29. 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

  30. 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.

Conference

Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 56

Proc. IEEE International Conference on Computer Vision (ICCV): 19

Proc. European Conference on Computer Vision (ECCV): 9

Proc. International Conference on Machine Learning (ICML): 3

Proc. Advances in Neural Information Processing Systems (NeurIPS): 7


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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

    1. Light-weight RefineNet with Pytorch code.

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

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

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

  27. 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

  28. 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

  29. 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

  30. 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

  31. 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

  32. 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

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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

  40. 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

  41. 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

  42. 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

  43. 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

  44. 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.

  45. 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

  46. 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

  47. 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

  48. 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

  49. 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

  50. 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

  51. 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

  52. 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

  53. 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

  54. 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

  55. 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

  56. 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

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

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

  59. 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

  60. 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

  61. 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

  62. 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

  63. 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

  64. 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

  65. 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

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

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

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

  69. 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. International Conference on Computer Vision (ICCV’19), 2019.
    cdot arXivbibtexsearchproject webpage

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

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

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

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

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

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

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

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

  78. 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

  79. 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

  80. 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

  81. 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

  82. 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

  83. 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

  84. 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.

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

  86. 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.

  87. 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.

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

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

  90. 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.

  91. 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

  92. 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

  93. 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

  94. 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