| DER: Dynamically Expandable Representation for Class Incremental Learning S Yan, J Xie, X He Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021 | 654 | 2021 |
| Distribution Alignment: A Unified Framework for Long-tail Visual Recognition S Zhang, Z Li, S Yan, X He, J Sun Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021 | 320 | 2021 |
| Dynamic context correspondence network for semantic alignment S Huang, Q Wang, S Zhang, S Yan, X He Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 98 | 2019 |
| Latentgnn: Learning efficient non-local relations for visual recognition S Zhang, X He, S Yan International Conference on Machine Learning, 7374-7383, 2019 | 91 | 2019 |
| A Dual Attention Network with Semantic Embedding for Few-Shot Learning. S Yan, S Zhang, X He AAAI 2019, 2019 | 72 | 2019 |
| {MegaScale}: Scaling large language model training to more than 10,000 {GPUs} Z Jiang, H Lin, Y Zhong, Q Huang, Y Chen, Z Zhang, Y Peng, X Li, C Xie, ... 21st USENIX Symposium on Networked Systems Design and Implementation (NSDI …, 2024 | 69 | 2024 |
| Missing Labels in Object Detection. M Xu, Y Bai, B Ghanem, B Liu, Y Gao, N Guo, X Ye, F Wan, H You, D Fan CVPR workshops 3 (5), 2019 | 57 | 2019 |
| An EM Framework for Online Incremental Learning of Semantic Segmentation S Yan, J Zhou, J Xie, S Zhang, X He ACM MM'21, 2021 | 49 | 2021 |
| General incremental learning with domain-aware categorical representations J Xie, S Yan, X He Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 45 | 2022 |
| How Well Does Self-Supervised Pre-Training Perform with Streaming Data? D Hu, S Yan, Q Lu, H Lanqing, H Hu, Y Zhang, Z Li, X Wang, J Feng ICLR 2022, 2022 | 32 | 2022 |
| Generative negative text replay for continual vision-language pretraining S Yan, L Hong, H Xu, J Han, T Tuytelaars, Z Li, X He European Conference on Computer Vision, 22-38, 2022 | 19 | 2022 |
| ATTA: anomaly-aware test-time adaptation for out-of-distribution detection in segmentation Z Gao, S Yan, X He Advances in Neural Information Processing Systems 36, 45150-45171, 2023 | 9 | 2023 |
| Budget-aware few-shot learning via graph convolutional network S Yan, S Zhang, X He arXiv preprint arXiv:2201.02304, 2022 | 7 | 2022 |
| MILD: modeling the instance learning dynamics for learning with noisy labels C Hu, S Yan, Z Gao, X He arXiv preprint arXiv:2306.11560, 2023 | 4 | 2023 |
| How Well Does Self-Supervised Pre-Training Perform with Streaming ImageNet? D Hu, S Yan, Q Lu, H Lanqing, H Hu, Y Zhang, Z Li, X Wang, J Feng NeurIPS 2021 Workshop on ImageNet: Past, Present, and Future, 0 | 2 | |
| Just Say What You Want: Only-prompting Self-rewarding Online Preference Optimization R Xu, Z Liu, Y Liu, S Yan, Z Wang, Z Zhang, X He arXiv preprint arXiv:2409.17534, 2024 | 1 | 2024 |
| Distribution Alignment: A Unified Framework for Long-tail Visual Recognition (Supplementary Material) S Zhang, Z Li, S Yan, X He, J Sun | | |
Xuming HeShanghaiTech UniversityПотвърден имейл адрес: shanghaitech.edu.cn
