The light field attachment: Turning a DSLR into a light field camera using a low budget camera ring Y Wang, Y Liu, W Heidrich, Q Dai IEEE transactions on visualization and computer graphics 23 (10), 2357-2364, 2016 | 77 | 2016 |
Moving indoor: Unsupervised video depth learning in challenging environments J Zhou, Y Wang, K Qin, W Zeng Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 76 | 2019 |
Blind quality assessment for image superresolution using deep two-stream convolutional networks W Zhou, Q Jiang, Y Wang, Z Chen, W Li Information Sciences 528, 205-218, 2020 | 74 | 2020 |
Unsupervised high-resolution depth learning from videos with dual networks J Zhou, Y Wang, K Qin, W Zeng Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 74 | 2019 |
Hyperspectral computational ghost imaging via temporal multiplexing Y Wang, J Suo, J Fan, Q Dai IEEE Photonics Technology Letters 28 (3), 288-291, 2015 | 63 | 2015 |
S2r-depthnet: Learning a generalizable depth-specific structural representation X Chen, Y Wang, X Chen, W Zeng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 59 | 2021 |
High speed computational ghost imaging via spatial sweeping Y Wang, Y Liu, J Suo, G Situ, C Qiao, Q Dai Scientific reports 7 (1), 45325, 2017 | 57 | 2017 |
Learning disentangled representation by exploiting pretrained generative models: A contrastive learning view X Ren, T Yang, Y Wang, W Zeng arXiv preprint arXiv:2102.10543, 2021 | 44 | 2021 |
Unifying layout generation with a decoupled diffusion model M Hui, Z Zhang, X Zhang, W Xie, Y Wang, Y Lu Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 38 | 2023 |
Artificial intelligence for metaverse: a framework Y Guo, T Yu, J Wu, Y Wang, S Wan, J Zheng, L Fang, Q Dai CAAI Artificial Intelligence Research 1 (1), 54-67, 2022 | 36 | 2022 |
Single-shot thermal ghost imaging using wavelength-division multiplexing C Deng, J Suo, Y Wang, Z Zhang, Q Dai Applied Physics Letters 112 (5), 2018 | 34 | 2018 |
Towards building a group-based unsupervised representation disentanglement framework T Yang, X Ren, Y Wang, W Zeng, N Zheng arXiv preprint arXiv:2102.10303, 2021 | 32 | 2021 |
Disdiff: Unsupervised disentanglement of diffusion probabilistic models T Yang, Y Wang, Y Lv, N Zheng arXiv preprint arXiv:2301.13721, 2023 | 30 | 2023 |
Zero-shot learning enables instant denoising and super-resolution in optical fluorescence microscopy C Qiao, Y Zeng, Q Meng, X Chen, H Chen, T Jiang, R Wei, J Guo, W Fu, ... Nature Communications 15 (1), 4180, 2024 | 28 | 2024 |
Template-guided hierarchical feature restoration for anomaly detection H Guo, L Ren, J Fu, Y Wang, Z Zhang, C Lan, H Wang, X Hou Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 23 | 2023 |
Visual concepts tokenization T Yang, Y Wang, Y Lu, N Zheng Advances in Neural Information Processing Systems 35, 31571-31582, 2022 | 19 | 2022 |
Retriever: Learning content-style representation as a token-level bipartite graph D Yin, X Ren, C Luo, Y Wang, Z Xiong, W Zeng arXiv preprint arXiv:2202.12307, 2022 | 15 | 2022 |
Do generative models know disentanglement? contrastive learning is all you need X Ren, T Yang, Y Wang, W Zeng arXiv preprint arXiv:2102.10543 14, 2021 | 15 | 2021 |
Test-time batch normalization T Yang, S Zhou, Y Wang, Y Lu, N Zheng arXiv preprint arXiv:2205.10210, 2022 | 14 | 2022 |
Doubling the pixel count limitation of single-pixel imaging via sinusoidal amplitude modulation Y Zhang, J Suo, Y Wang, Q Dai Optics Express 26 (6), 6929-6942, 2018 | 14 | 2018 |