| Learning deep context-aware features over body and latent parts for person re-identification D Li, X Chen, Z Zhang, K Huang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 790 | 2017 |
| Focal and efficient IOU loss for accurate bounding box regression YF Zhang, W Ren, Z Zhang, Z Jia, L Wang, T Tan Neurocomputing 506, 146-157, 2022 | 721 | 2022 |
| Slow feature analysis for human action recognition Z Zhang, D Tao IEEE transactions on pattern analysis and machine intelligence 34 (3), 436-450, 2012 | 373 | 2012 |
| Comparison of similarity measures for trajectory clustering in outdoor surveillance scenes Z Zhang, K Huang, T Tan International Conference on Pattern Recognition, 1135-1138, 2006 | 364 | 2006 |
| Towards rich feature discovery with class activation maps augmentation for person re-identification W Yang, H Huang, Z Zhang, X Chen, K Huang, S Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 285 | 2019 |
| Adversarially occluded samples for person re-identification H Huang, D Li, Z Zhang, X Chen, K Huang Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 274 | 2018 |
| Stronger, faster and more explainable: A graph convolutional baseline for skeleton-based action recognition YF Song, Z Zhang, C Shan, L Wang proceedings of the 28th ACM international conference on multimedia, 1625-1633, 2020 | 259 | 2020 |
| Constructing stronger and faster baselines for skeleton-based action recognition YF Song, Z Zhang, C Shan, L Wang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022 | 237 | 2022 |
| A richly annotated dataset for pedestrian attribute recognition D Li, Z Zhang, X Chen, H Ling, K Huang arXiv preprint arXiv:1603.07054, 2016 | 222 | 2016 |
| A richly annotated pedestrian dataset for person retrieval in real surveillance scenarios D Li, Z Zhang, X Chen, K Huang IEEE transactions on image processing 28 (4), 1575-1590, 2018 | 168 | 2018 |
| Richly activated graph convolutional network for robust skeleton-based action recognition YF Song, Z Zhang, C Shan, L Wang IEEE Transactions on Circuits and Systems for Video Technology 31 (5), 1915-1925, 2020 | 163 | 2020 |
| Pose guided deep model for pedestrian attribute recognition in surveillance scenarios D Li, X Chen, Z Zhang, K Huang 2018 IEEE international conference on multimedia and expo (ICME), 1-6, 2018 | 151 | 2018 |
| Richly activated graph convolutional network for action recognition with incomplete skeletons YF Song, Z Zhang, L Wang 2019 IEEE International Conference on Image Processing (ICIP), 1-5, 2019 | 139 | 2019 |
| A large-scale distributed video parsing and evaluation platform K Yu, Y Zhou, D Li, Z Zhang, K Huang Intelligent Visual Surveillance: 4th Chinese Conference, IVS 2016, Beijing …, 2016 | 120 | 2016 |
| Multi angle optimal pattern-based deep learning for automatic facial expression recognition DK Jain, Z Zhang, K Huang Pattern Recognition Letters 139, 157-165, 2020 | 102 | 2020 |
| Deep fusion feature representation learning with hard mining center-triplet loss for person re-identification C Zhao, X Lv, Z Zhang, W Zuo, J Wu, D Miao IEEE Transactions on Multimedia 22 (12), 3180-3195, 2020 | 99 | 2020 |
| Weakly-supervised learning of mid-level features for pedestrian attribute recognition and localization K Yu, B Leng, Z Zhang, D Li, K Huang arXiv preprint arXiv:1611.05603, 2016 | 92 | 2016 |
| An extended grammar system for learning and recognizing complex visual events Z Zhang, T Tan, K Huang IEEE transactions on pattern analysis and machine intelligence 33 (2), 240-255, 2011 | 76 | 2011 |
| Trajectory series analysis based event rule induction for visual surveillance Z Zhang, K Huang, T Tan, L Wang 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007 | 54 | 2007 |
| Deep unbiased embedding transfer for zero-shot learning Z Jia, Z Zhang, L Wang, C Shan, T Tan IEEE Transactions on Image Processing 29, 1958-1971, 2019 | 45 | 2019 |
