| Residual Attention: A Simple but Effective Method for Multi-Label Recognition K Zhu, J Wu Proceedings of the IEEE/CVF International Conference on Computer Vision, 184-193, 2021 | 131 | 2021 |
| Multi-Label Self-Supervised Learning with Scene Images K Zhu, M Fu, J Wu Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 4 | 2023 |
| Quantized Feature Distillation for Network Quantization K Zhu, YY He, J Wu Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023, 2023 | 3 | 2023 |
| DTL: Disentangled Transfer Learning for Visual Recognition M Fu, K Zhu, J Wu AAAI 2024, 2023 | 2 | 2023 |
| Coarse Is Better? A New Pipeline Towards Self-Supervised Learning with Uncurated Images K Zhu, YY He, J Wu arXiv preprint arXiv:2306.04244, 2023 | 2 | 2023 |
| Rectify the Regression Bias in Long-Tailed Object Detection K Zhu, M Fu, J Shao, T Liu, J Wu arXiv preprint arXiv:2401.15885, 2024 | 1 | 2024 |
| Instance-based Max-margin for Practical Few-shot Recognition M Fu, K Zhu* CVPR2024, 2023 | 1 | 2023 |
| Self-Supervised Visual Preference Alignment K Zhu, L Zhao, Z Ge, X Zhang arXiv preprint arXiv:2404.10501, 2024 | | 2024 |
| DiffuLT: How to Make Diffusion Model Useful for Long-tail Recognition J Shao, K Zhu, H Zhang, J Wu arXiv preprint arXiv:2403.05170, 2024 | | 2024 |
| Low-rank Attention Side-Tuning for Parameter-Efficient Fine-Tuning N Tang, M Fu, K Zhu, J Wu arXiv preprint arXiv:2402.04009, 2024 | | 2024 |
Jianxin Wu (吴建鑫)Nanjing UniversityDirección de correo verificada de nju.edu.cn
