| Foster: Feature boosting and compression for class-incremental learning FY Wang, DW Zhou, HJ Ye, DC Zhan European conference on computer vision, 398-414, 2022 | 239 | 2022 |
| Learning Placeholders for Open-Set Recognition DW Zhou, HJ Ye, DC Zhan IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021 | 236 | 2021 |
| Forward compatible few-shot class-incremental learning DW Zhou, FY Wang, HJ Ye, L Ma, S Pu, DC Zhan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 192 | 2022 |
| Class-incremental learning: A survey DW Zhou, QW Wang, ZH Qi, HJ Ye, DC Zhan, Z Liu IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 184* | 2024 |
| A model or 603 exemplars: Towards memory-efficient class-incremental learning DW Zhou, QW Wang, HJ Ye, DC Zhan The Eleventh International Conference on Learning Representations, 2023 | 119 | 2023 |
| Adaptive deep models for incremental learning: Considering capacity scalability and sustainability Y Yang, DW Zhou, DC Zhan, H Xiong, Y Jiang Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019 | 94 | 2019 |
| Few-shot class-incremental learning by sampling multi-phase tasks DW Zhou, HJ Ye, L Ma, D Xie, S Pu, DC Zhan IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (11 …, 2023 | 91 | 2023 |
| Pycil: A python toolbox for class-incremental learning DW Zhou, FY Wang, HJ Ye, DC Zhan Science China Information Sciences 66 (9), 197101, 2023 | 69 | 2023 |
| Co-transport for class-incremental learning DW Zhou, HJ Ye, DC Zhan Proceedings of the 29th ACM International Conference on Multimedia, 1645-1654, 2021 | 62 | 2021 |
| Learning to Classify with Incremental New Class DW Zhou, Y Yang, DC Zhan IEEE Transactions on Neural Networks and Learning Systems, 2021 | 52 | 2021 |
| Beef: Bi-compatible class-incremental learning via energy-based expansion and fusion FY Wang, DW Zhou, L Liu, HJ Ye, Y Bian, DC Zhan, P Zhao The Eleventh International Conference on Learning Representations, 2023 | 40 | 2023 |
| Cost-effective incremental deep model: Matching model capacity with the least sampling Y Yang, DW Zhou, DC Zhan, H Xiong, Y Jiang, J Yang IEEE Transactions on Knowledge and Data Engineering 35 (4), 3575-3588, 2021 | 30 | 2021 |
| Learning without forgetting for vision-language models DW Zhou, Y Zhang, J Ning, HJ Ye, DC Zhan, Z Liu arXiv preprint arXiv:2305.19270, 2023 | 27 | 2023 |
| Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration QW Wang, DW Zhou, YK Zhang, DC Zhan, HJ Ye Neural Information Processing Systems (NeurIPS), 15060-15076, 2023 | 24 | 2023 |
| RF-Badge: Vital sign-based authentication via RFID tag array on badges J Ning, L Xie, C Wang, Y Bu, F Xu, DW Zhou, S Lu, B Ye IEEE Transactions on Mobile Computing, 2021 | 22 | 2021 |
| Continual Learning with Pre-Trained Models: A Survey DW Zhou, HL Sun, J Ning, HJ Ye, DC Zhan International Joint Conference on Artificial Intelligence (IJCAI), 2024 | 20 | 2024 |
| Expandable subspace ensemble for pre-trained model-based class-incremental learning DW Zhou, HL Sun, HJ Ye, DC Zhan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 14 | 2024 |
| Pilot: A pre-trained model-based continual learning toolbox HL Sun, DW Zhou, HJ Ye, DC Zhan arXiv preprint arXiv:2309.07117, 2023 | 14 | 2023 |
| Revisiting class-incremental learning with pre-trained models: Generalizability and adaptivity are all you need DW Zhou, ZW Cai, HJ Ye, DC Zhan, Z Liu International Journal of Computer Vision, 1-21, 2024 | 8 | 2024 |
| Contextualizing meta-learning via learning to decompose HJ Ye, DW Zhou, L Hong, Z Li, XS Wei, DC Zhan IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 7 | 2023 |
De-Chuan ZhanNanjing University, ChinaVerified email at nju.edu.cn
