| Domain-symmetric networks for adversarial domain adaptation Y Zhang, H Tang, K Jia, M Tan Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 406 | 2019 |
| Exact feature distribution matching for arbitrary style transfer and domain generalization Y Zhang, M Li, R Li, K Jia, L Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 144 | 2022 |
| Fine-grained visual categorization using meta-learning optimization with sample selection of auxiliary data Y Zhang, H Tang, K Jia Proceedings of the european conference on computer vision (ECCV), 233-248, 2018 | 116 | 2018 |
| Label propagation with augmented anchors: A simple semi-supervised learning baseline for unsupervised domain adaptation Y Zhang, B Deng, K Jia, L Zhang European Conference on Computer Vision, 781-797, 2020 | 82 | 2020 |
| Class-balanced pixel-level self-labeling for domain adaptive semantic segmentation R Li, S Li, C He, Y Zhang, X Jia, L Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 77 | 2022 |
| Unsupervised multi-class domain adaptation: Theory, algorithms, and practice Y Zhang, B Deng, H Tang, L Zhang, K Jia IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (5), 2775-2792, 2020 | 72 | 2020 |
| Tango: Text-driven photorealistic and robust 3d stylization via lighting decomposition Y Chen, R Chen, J Lei, Y Zhang, K Jia Advances in Neural Information Processing Systems 35, 30923-30936, 2022 | 66 | 2022 |
| Unsupervised Domain Adaptation of Black-Box Source Models H Zhang, Y Zhang, K Jia, L Zhang BMVC2021, 2021 | 59 | 2021 |
| Semi-supervised models are strong unsupervised domain adaptation learners Y Zhang, H Zhang, B Deng, S Li, K Jia, L Zhang arXiv preprint arXiv:2106.00417, 2021 | 28 | 2021 |
| Part-aware fine-grained object categorization using weakly supervised part detection network Y Zhang, K Jia, Z Wang IEEE Transactions on Multimedia 22 (5), 1345-1357, 2019 | 27 | 2019 |
| Masked surfel prediction for self-supervised point cloud learning Y Zhang, J Lin, C He, Y Chen, K Jia, L Zhang arXiv preprint arXiv:2207.03111, 2022 | 13 | 2022 |
| On universal black-box domain adaptation B Deng, Y Zhang, H Tang, C Ding, K Jia arXiv preprint arXiv:2104.04665, 2021 | 13 | 2021 |
| DynaMask: dynamic mask selection for instance segmentation R Li, C He, S Li, Y Zhang, L Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 11 | 2023 |
| Gradual domain adaptation via self-training of auxiliary models Y Zhang, B Deng, K Jia, L Zhang arXiv preprint arXiv:2106.09890, 2021 | 11 | 2021 |
| Adversarial style augmentation for domain generalization Y Zhang, B Deng, R Li, K Jia, L Zhang arXiv preprint arXiv:2301.12643, 2023 | 9 | 2023 |
| Vi-net: Boosting category-level 6d object pose estimation via learning decoupled rotations on the spherical representations J Lin, Z Wei, Y Zhang, K Jia Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 9 | 2023 |
| Sim: Semantic-aware instance mask generation for box-supervised instance segmentation R Li, C He, Y Zhang, S Li, L Chen, L Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 6 | 2023 |
| Msf: Motion-guided sequential fusion for efficient 3d object detection from point cloud sequences C He, R Li, Y Zhang, S Li, L Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 5 | 2023 |
| Point-dae: Denoising autoencoders for self-supervised point cloud learning Y Zhang, J Lin, R Li, K Jia, L Zhang arXiv e-prints, arXiv: 2211.06841, 2022 | 4 | 2022 |
| Dual memory networks: A versatile adaptation approach for vision-language models Y Zhang, W Zhu, H Tang, Z Ma, K Zhou, L Zhang Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2024 | 3 | 2024 |
Kui Jia (贾奎)The Chinese University of Hong Kong, Shenzhen在 cuhk.edu.cn 的电子邮件经过验证
