| 3d shapenets: A deep representation for volumetric shapes Z Wu, S Song, A Khosla, F Yu, L Zhang, X Tang, J Xiao Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 5705 | 2015 |
| Unsupervised feature learning via non-parametric instance discrimination Z Wu, Y Xiong, SX Yu, D Lin Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 3273 | 2018 |
| Temporal action detection with structured segment networks Y Zhao, Y Xiong, L Wang, Z Wu, X Tang, D Lin Proceedings of the IEEE international conference on computer vision, 2914-2923, 2017 | 961 | 2017 |
| The seventh visual object tracking VOT2019 challenge results M Kristan, J Matas, A Leonardis, M Felsberg, R Pflugfelder, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 477 | 2019 |
| The eighth visual object tracking VOT2020 challenge results M Kristan, A Leonardis, J Matas, M Felsberg, R Pflugfelder, ... Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 231 | 2020 |
| What makes instance discrimination good for transfer learning? N Zhao, Z Wu, RWH Lau, S Lin International Conference on Representation Learning (2021), 2020 | 148 | 2020 |
| Improving generalization via scalable neighborhood component analysis Z Wu, AA Efros, SX Yu Proceedings of the european conference on computer vision (ECCV), 685-701, 2018 | 141 | 2018 |
| Instance localization for self-supervised detection pretraining C Yang, Z Wu, B Zhou, S Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 123 | 2021 |
| A transductive approach for video object segmentation Y Zhang, Z Wu, H Peng, S Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 114 | 2020 |
| Aligning Pretraining for Detection via Object-Level Contrastive Learning F Wei, Y Gao, Z Wu, H Hu, S Lin Thirty-Fifth Conference on Neural Information Processing Systems, 2021 | 103 | 2021 |
| Deep metric transfer for label propagation with limited annotated data B Liu, Z Wu, H Hu, S Lin Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 73 | 2019 |
| A simple multi-modality transfer learning baseline for sign language translation Y Chen, F Wei, X Sun, Z Wu, S Lin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 52 | 2022 |
| Distilling localization for self-supervised representation learning N Zhao, Z Wu, RWH Lau, S Lin The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20), 2020 | 47 | 2020 |
| Cuhk & ethz & siat submission to activitynet challenge 2017 Y Zhao, B Zhang, Z Wu, S Yang, L Zhou, S Yan, L Wang, Y Xiong, D Lin, ... arXiv preprint arXiv:1710.08011 8 (8), 2017 | 45 | 2017 |
| Debiased learning from naturally imbalanced pseudo-labels X Wang, Z Wu, L Lian, SX Yu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 41* | 2022 |
| Unsupervised 3d learning for shape analysis via multiresolution instance discrimination PS Wang, YQ Yang, QF Zou, Z Wu, Y Liu, X Tong Proceedings of the AAAI Conference on Artificial Intelligence 35 (4), 2773-2781, 2021 | 37 | 2021 |
| The emergence of objectness: Learning zero-shot segmentation from videos R Liu, Z Wu, S Yu, S Lin Advances in Neural Information Processing Systems 34, 13137-13152, 2021 | 32 | 2021 |
| Deep markov random field for image modeling Z Wu, D Lin, X Tang Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 31 | 2016 |
| One-shot generative domain adaptation C Yang, Y Shen, Z Zhang, Y Xu, J Zhu, Z Wu, B Zhou Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 22 | 2023 |
| Adjustable bounded rectifiers: Towards deep binary representations Z Wu, D Lin, X Tang arXiv preprint arXiv:1511.06201, 2015 | 16 | 2015 |
Xiaoou TangThe Chinese University of Hong KongEmail verificata su ie.cuhk.edu.hk
