| In-domain gan inversion for real image editing J Zhu, Y Shen, D Zhao, B Zhou European conference on computer vision, 592-608, 2020 | 693 | 2020 |
| Generative hierarchical features from synthesizing images Y Xu, Y Shen, J Zhu, C Yang, B Zhou Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 113 | 2021 |
| Low-rank subspaces in gans J Zhu, R Feng, Y Shen, D Zhao, ZJ Zha, J Zhou, Q Chen Advances in Neural Information Processing Systems 34, 16648-16658, 2021 | 74 | 2021 |
| Disentangled inference for GANs with latently invertible autoencoder J Zhu, D Zhao, B Zhang, B Zhou International Journal of Computer Vision 130 (5), 1259-1276, 2022 | 43* | 2022 |
| One-shot generative domain adaptation C Yang, Y Shen, Z Zhang, Y Xu, J Zhu, Z Wu, B Zhou Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 37 | 2023 |
| Region-based semantic factorization in gans J Zhu, Y Shen, Y Xu, D Zhao, Q Chen arXiv preprint arXiv:2202.09649, 2022 | 36 | 2022 |
| High-fidelity gan inversion with padding space Q Bai, Y Xu, J Zhu, W Xia, Y Yang, Y Shen European Conference on Computer Vision, 36-53, 2022 | 32 | 2022 |
| 3d-aware indoor scene synthesis with depth priors Z Shi, Y Shen, J Zhu, DY Yeung, Q Chen European Conference on Computer Vision, 406-422, 2022 | 32 | 2022 |
| Linkgan: Linking gan latents to pixels for controllable image synthesis J Zhu, C Yang, Y Shen, Z Shi, B Dai, D Zhao, Q Chen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 18 | 2023 |
| Uncertainty principles of encoding GANs R Feng, Z Lin, J Zhu, D Zhao, J Zhou, ZJ Zha International Conference on Machine Learning, 3240-3251, 2021 | 8 | 2021 |
| Exploring sparse moe in gans for text-conditioned image synthesis J Zhu, C Yang, K Zheng, Y Xu, Z Shi, Y Shen arXiv preprint arXiv:2309.03904, 2023 | 3 | 2023 |
| Latent Variables on Spheres for Sampling and Inference D Zhao, J Zhu, B Zhang | 3* | |
| Learning modulated transformation in GANs C Yang, Q Zhang, Y Xu, J Zhu, Y Shen, B Dai Advances in Neural Information Processing Systems 36, 2024 | 1 | 2024 |
| In-Domain GAN Inversion for Faithful Reconstruction and Editability J Zhu, Y Shen, Y Xu, D Zhao, Q Chen, B Zhou IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 1 | 2024 |
| Interpreting class conditional GANs with channel awareness Y He, Z Zhang, J Zhu, Y Shen, Q Chen arXiv preprint arXiv:2203.11173, 2022 | 1 | 2022 |
| In-Domain GAN Inversion for Real Image Editing Supplementary Material J Zhu, Y Shen, D Zhao, B Zhou | 1 | 2020 |
| Curriculum Learning for Deep Generative Models with Clustering D Zhao, J Zhu, Z Guo, B Zhang arXiv preprint arXiv:1906.11594, 2019 | 1 | 2019 |
| GH-Feat: Learning Versatile Generative Hierarchical Features From GANs Y Xu, Y Shen, J Zhu, C Yang, B Zhou IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (6), 7395-7411, 2022 | | 2022 |
| LinkGAN: Linking GAN Latents to Pixels for Controllable Image Synthesis Supplementary Material J Zhu, C Yang, Y Shen, Z Shi, BDDZQ Chen | | |
| One-Shot Generative Domain Adaptation–Supplementary Material– C Yang, Y Shen, Z Zhang, Y Xu, J Zhu, Z Wu, B Zhou | | |
Yujun ShenAnt Group在 link.cuhk.edu.hk 的电子邮件经过验证
