| Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Y Su, X Xu, K Jia Advances in Neural Information Processing Systems 2022, 2022 | 33 | 2022 |
| Weakly supervised 3D point cloud segmentation via multi-prototype learning Y Su, X Xu, K Jia IEEE Transactions on Circuits and Systems for Video Technology, 2023 | 24 | 2023 |
| Towards real-world test-time adaptation: Tri-net self-training with balanced normalization Y Su, X Xu, K Jia Proceedings of the AAAI Conference on Artificial Intelligence 38 (13), 15126 …, 2024 | 8 | 2024 |
| On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion Y Li, X Xu, Y Su, K Jia IEEE/CVF International Conference on Computer Vision 2023, 2023 | 8 | 2023 |
| Revisiting Realistic Test-Time Training: Sequential Inference and Adaptation by Anchored Clustering Regularized Self-Training Y Su, X Xu, T Li, K Jia IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 7 | 2024 |
| Improving the Generalization of Segmentation Foundation Model under Distribution Shift via Weakly Supervised Adaptation H Zhang, Y Su, X Xu, K Jia IEEE/CVF Conference on Computer Vision and Pattern Recognition 2024, 2024 | 4 | 2024 |
| STFAR: Improving Object Detection Robustness at Test-Time by Self-Training with Feature Alignment Regularization Y Chen, X Xu, Y Su, K Jia arXiv preprint arXiv:2303.17937, 2023 | 2 | 2023 |
| Exploring Human-in-the-Loop Test-Time Adaptation by Synergizing Active Learning and Model Selection Y Li, Y Su, X Yang, K Jia, X Xu arXiv preprint arXiv:2405.18911, 2024 | | 2024 |
| CLIP-guided Source-free Object Detection in Aerial Images N Liu, X Xu, Y Su, C Liu, P Gong, HC Li The International Geoscience and Remote Sensing Symposium (IGARSS) 2024, 2024 | | 2024 |
| Appendix of” On the Robustness of Open-World Test-Time Training: Self-Training with Dynamic Prototype Expansion” Y Li, X Xu, Y Su, K Jia | | |
Xun XuSenior Scientist at I2R, A-STARE-mailová adresa ověřena na: i2r.a-star.edu.sg
