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 | 445 | 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 | 262 | 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 | 88 | 2019 |
Latentgnn: Learning efficient non-local relations for visual recognition S Zhang, X He, S Yan International Conference on Machine Learning, 7374-7383, 2019 | 84 | 2019 |
A Dual Attention Network with Semantic Embedding for Few-Shot Learning. S Yan, S Zhang, X He AAAI 2019, 2019 | 67 | 2019 |
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 | 48 | 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 | 39 | 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 | 28 | 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 | 23 | 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 | 10 | 2022 |
Budget-aware few-shot learning via graph convolutional network S Yan, S Zhang, X He arXiv preprint arXiv:2201.02304, 2022 | 4 | 2022 |
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, ... arXiv preprint arXiv:2402.15627, 2024 | 1 | 2024 |
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 | 1 | 2023 |
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 | | 2023 |
Distribution Alignment: A Unified Framework for Long-tail Visual Recognition (Supplementary Material) S Zhang, Z Li, S Yan, X He, J Sun | | |