| Bmn: Boundary-matching network for temporal action proposal generation T Lin, X Liu, X Li, E Ding, S Wen ICCV, 2019, 3889-3898, 2019 | 692 | 2019 |
| Deep Metric Learning with Angular Loss J Wang, F Zhou, S Wen, X Liu, Y Lin ICCV, 2017, 2017 | 622 | 2017 |
| Deep Speaker: an End-to-End Neural Speaker Embedding System C Li, X Ma, B Jiang, X Li, X Zhang, X Liu, Y Cao, A Kannan, Z Zhu arXiv preprint arXiv:1705.02304, 2017 | 558 | 2017 |
| Kernel Pooling for Convolutional Neural Networks Y Cui, F Zhou, J Wang, X Liu, Y Lin, S Belongie CVPR, 2017, 2017 | 375 | 2017 |
| STGAN: A Unified Selective Transfer Network for Arbitrary Image Attribute Editing M Liu, Y Ding, M Xia, X Liu, E Ding, W Zuo, S Wen CVPR, 2019, 2019 | 366 | 2019 |
| Fine-Grained Recognition with Automatic and Efficient Part Attention X Liu, T Xia, J Wang, Y Yang, F Zhou, Y Lin arXiv preprint arXiv:1603.06765, 2016, 2017 | 279* | 2017 |
| Attention Clusters: Purely Attention Based Local Feature Integration for Video Classification X Long, C Gan, G de Melo, J Wu, X Liu, S Wen CVPR, 2018, 2018 | 273 | 2018 |
| Image inpainting with learnable bidirectional attention maps C Xie, S Liu, C Li, MM Cheng, W Zuo, X Liu, S Wen, E Ding ICCV, 2019, 8858-8867, 2019 | 270 | 2019 |
| Semi-supervised coupled dictionary learning for person re-identification X Liu, M Song, D Tao, X Zhou, C Chen, J Bu CVPR, 2014, 3550-3557, 2014 | 266 | 2014 |
| Probabilistic graphlet transfer for photo cropping L Zhang, M Song, Q Zhao, X Liu, J Bu, C Chen IEEE Transactions on Image Processing 22 (2), 802-815, 2012 | 195 | 2012 |
| Probabilistic graphlet cut: Exploiting spatial structure cue for weakly supervised image segmentation L Zhang, M Song, Z Liu, X Liu, J Bu, C Chen CVPR, 2013, 1908-1915, 2013 | 186 | 2013 |
| Dynamic Instance Normalization for Arbitrary Style Transfer Y Jing, X Liu, Y Ding, X Wang, E Ding, M Song, S Wen AAAI, 2020, 2019 | 174 | 2019 |
| StNet: Local and Global Spatial-Temporal Modeling for Action Recognition D He, Z Zhou, C Gan, F Li, X Liu, Y Li, L Wang, S Wen AAAI, 2019, 2019 | 161 | 2019 |
| Read, Watch, and Move: Reinforcement Learning for Temporally Grounding Natural Language Descriptions in Videos D He, X Zhao, J Huang, F Li, X Liu, S Wen AAAI, 2019, 2019 | 154 | 2019 |
| Multimodal keyless attention fusion for video classification X Long, C Gan, G de Melo, X Liu, Y Li, F Li, S Wen AAAI, 2018, 2018 | 142 | 2018 |
| Dynamic computational time for visual attention Z Li, Y Yang, X Liu, F Zhou, S Wen, W Xu Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 138 | 2017 |
| NTIRE 2019 Challenge on Real Image Super-Resolution: Methods and Results J Cai, S Gu, L Radu, Timofte, Zhang, X Liu, D Yukang, H Dongliang, C Li, ... CVPR 2019 Workshop, 2019 | 121 | 2019 |
| Learning contextual dependence with convolutional hierarchical recurrent neural networks Z Zuo, B Shuai, G Wang, X Liu, X Wang, B Wang, Y Chen IEEE Transactions on Image Processing 25 (7), 2983-2996, 2016 | 116 | 2016 |
| Semi-supervised node splitting for random forest construction X Liu, M Song, D Tao, Z Liu, L Zhang, C Chen, J Bu CVPR, 2013, 492-499, 2013 | 112* | 2013 |
| Image Inpainting by End-to-End Cascaded Refinement With Mask Awareness M Zhu, D He, X Li, C Li, F Li, X Liu, E Ding, Z Zhang IEEE Transactions on Image Processing 30, 4855-4866, 2021 | 103 | 2021 |
