| Domain invariant and class discriminative feature learning for visual domain adaptation S Li, S Song, G Huang, Z Ding, C Wu IEEE transactions on image processing 27 (9), 4260-4273, 2018 | 231 | 2018 |
| Deep residual correction network for partial domain adaptation S Li, CH Liu, Q Lin, Q Wen, L Su, G Huang, Z Ding IEEE transactions on pattern analysis and machine intelligence 43 (7), 2329-2344, 2020 | 147 | 2020 |
| Metasaug: Meta semantic augmentation for long-tailed visual recognition S Li, K Gong, CH Liu, Y Wang, F Qiao, X Cheng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 138 | 2021 |
| Joint adversarial domain adaptation S Li, CH Liu, B Xie, L Su, Z Ding, G Huang Proceedings of the 27th ACM International Conference on Multimedia, 729-737, 2019 | 120 | 2019 |
| Causality inspired representation learning for domain generalization F Lv, J Liang, S Li, B Zang, CH Liu, Z Wang, D Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 113 | 2022 |
| Transferable semantic augmentation for domain adaptation S Li, M Xie, K Gong, CH Liu, Y Wang, W Li Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 109 | 2021 |
| SOE-Net: A self-attention and orientation encoding network for point cloud based place recognition Y Xia, Y Xu, S Li, R Wang, J Du, D Cremers, U Stilla Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2021 | 107 | 2021 |
| Domain space transfer extreme learning machine for domain adaptation Y Chen, S Song, S Li, L Yang, C Wu IEEE Transactions on Cybernetics 49 (5), 1909-1922, 2018 | 106 | 2018 |
| Sepico: Semantic-guided pixel contrast for domain adaptive semantic segmentation B Xie, S Li, M Li, CH Liu, G Huang, G Wang IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 105 | 2023 |
| Domain conditioned adaptation network S Li, C Liu, Q Lin, B Xie, Z Ding, G Huang, J Tang Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 11386 …, 2020 | 99 | 2020 |
| Domain adaptation via prompt learning C Ge, R Huang, M Xie, Z Lai, S Song, S Li, G Huang IEEE Transactions on Neural Networks and Learning Systems, 2023 | 94 | 2023 |
| Bi-Classifier Determinacy Maximization for Unsupervised Domain Adaptation S Li, F Lv, B Xie, CH Liu, J Liang, C Qin arXiv preprint arXiv:2012.06995, 2020 | 89 | 2020 |
| Active learning for domain adaptation: An energy-based approach B Xie, L Yuan, S Li, CH Liu, X Cheng, G Wang Proceedings of the AAAI conference on artificial intelligence 36 (8), 8708-8716, 2022 | 87 | 2022 |
| Semantic concentration for domain adaptation S Li, M Xie, F Lv, CH Liu, J Liang, C Qin, W Li Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 81 | 2021 |
| Prediction reweighting for domain adaptation S Li, S Song, G Huang IEEE transactions on neural networks and learning systems 28 (7), 1682-1695, 2016 | 80 | 2016 |
| A graph embedding framework for maximum mean discrepancy-based domain adaptation algorithms Y Chen, S Song, S Li, C Wu IEEE Transactions on Image Processing 29, 199-213, 2019 | 70 | 2019 |
| Discriminative transfer feature and label consistency for cross-domain image classification S Li, CH Liu, L Su, B Xie, Z Ding, CLP Chen, D Wu IEEE Transactions on Neural Networks and Learning Systems 31 (11), 4842-4856, 2020 | 62 | 2020 |
| Towards fewer annotations: Active learning via region impurity and prediction uncertainty for domain adaptive semantic segmentation B Xie, L Yuan, S Li, CH Liu, X Cheng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 58 | 2022 |
| Generalized domain conditioned adaptation network S Li, B Xie, Q Lin, CH Liu, G Huang, G Wang IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (8), 4093-4109, 2021 | 58 | 2021 |
| Twin extreme learning machines for pattern classification Y Wan, S Song, G Huang, S Li Neurocomputing 260, 235-244, 2017 | 53 | 2017 |
Binhui Xie （谢斌辉）Ph.D. Beijing Institute of TechnologyVerified email at bit.edu.cn
