Selected Publications

Google scholar (11746 citations) , DBLP, arXiv.

Journal

  1. 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

  2. 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 bibtexsearch

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

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

  17. 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

  18. 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

  19. 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

  20. 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

  21. 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

  22. 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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

  28. 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

  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 bibtexsearch

  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 bibtexsearch

  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 arXivbibtexsearch

  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 bibtexsearch

  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. 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

  22. Asking the difficult questions: 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

  23. 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

  24. 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

  25. 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

  26. 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

  27. 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

  28. 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

  29. 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

  30. 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

  31. 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

  32. 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

  33. 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

  34. 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

  35. 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

  36. 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

  37. 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

  38. 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

  39. 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

  40. 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

  41. 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

  42. 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

  43. 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.

  44. 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

  45. 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

  46. 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

  47. 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

  48. 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

  49. 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

  50. 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

  51. 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

  52. 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

  53. 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

  54. 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

  55. 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

  56. 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

  57. 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

  58. 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

  59. 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

  60. 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.

  61. 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

  62. 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

  63. 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

  64. 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

  65. 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

  66. 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

  67. 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.

  68. 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

  69. 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

  70. 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

  71. 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.

  72. 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

  73. 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

  74. 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

  75. 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

  76. 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

  77. 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

  78. 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

  79. 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

  80. 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

  81. 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

  82. 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

  83. 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

  84. 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

  85. 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.