| Weighted nuclear norm minimization with application to image denoising S Gu, L Zhang, W Zuo, X Feng Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 3014 | 2014 |
| Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang, B Lim, S Son, ... 2017 IEEE conference on computer vision and pattern recognition workshops …, 2017 | 2951 | 2017 |
| Learning deep CNN denoiser prior for image restoration K Zhang, W Zuo, S Gu, L Zhang 2017 IEEE conference on computer vision and pattern recognition (CVPR), 2808 …, 2017 | 2872 | 2017 |
| Learning a deep single image contrast enhancer from multi-exposure images J Cai, S Gu, L Zhang IEEE transactions on image processing 27 (4), 2049-2062, 2018 | 1531 | 2018 |
| Weighted nuclear norm minimization and its applications to low level vision S Gu, Q Xie, D Meng, W Zuo, X Feng, L Zhang International journal of computer vision 121 (2), 183-208, 2017 | 981 | 2017 |
| Learning convolutional networks for content-weighted image compression M Li, W Zuo, S Gu, D Zhao, D Zhang 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 3214-3223, 2018 | 537 | 2018 |
| Weighted Schatten-Norm Minimization for Image Denoising and Background Subtraction Y Xie, S Gu, Y Liu, W Zuo, W Zhang, L Zhang IEEE transactions on image processing 25 (10), 4842-4857, 2016 | 512 | 2016 |
| Convolutional sparse coding for image super-resolution S Gu, W Zuo, Q Xie, D Meng, X Feng, L Zhang Proceedings of the IEEE international conference on computer vision, 1823-1831, 2015 | 476 | 2015 |
| Projective dictionary pair learning for pattern classification S Gu, L Zhang, W Zuo, X Feng Advances in neural information processing systems 27, 2014 | 402 | 2014 |
| You only look yourself: Unsupervised and untrained single image dehazing neural network B Li, Y Gou, S Gu, JZ Liu, JT Zhou, X Peng International Journal of Computer Vision 129 (5), 1754-1767, 2021 | 363 | 2021 |
| Video super-resolution with recurrent structure-detail network T Isobe, X Jia, S Gu, S Li, S Wang, Q Tian European conference on computer vision, 645-660, 2020 | 350 | 2020 |
| Frequency separation for real-world super-resolution M Fritsche, S Gu, R Timofte 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW …, 2019 | 343 | 2019 |
| Group sparsity: The hinge between filter pruning and decomposition for network compression Y Li, S Gu, C Mayer, LV Gool, R Timofte Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 327 | 2020 |
| Multispectral images denoising by intrinsic tensor sparsity regularization Q Xie, Q Zhao, D Meng, Z Xu, S Gu, W Zuo, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 307 | 2016 |
| Joint convolutional analysis and synthesis sparse representation for single image layer separation S Gu, D Meng, W Zuo, L Zhang 2017 IEEE International conference on computer vision (ICCV), 1717-1725, 2017 | 296 | 2017 |
| Self-guided network for fast image denoising S Gu, Y Li, LV Gool, R Timofte Proceedings of the IEEE/CVF International Conference on computer Vision …, 2019 | 273 | 2019 |
| Video rain streak removal by multiscale convolutional sparse coding M Li, Q Xie, Q Zhao, W Wei, S Gu, J Tao, D Meng 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 6644-6653, 2018 | 252 | 2018 |
| Unsupervised real-world image super resolution via domain-distance aware training Y Wei, S Gu, Y Li, R Timofte, L Jin, H Song Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 235 | 2021 |
| Flow-based kernel prior with application to blind super-resolution J Liang, K Zhang, S Gu, L Van Gool, R Timofte 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2021 | 214 | 2021 |
| Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary L Zhang, Y Li, X Zhou, X Zhao, S Gu CVPR 2024, 2024 | 212 | 2024 |
Radu TimofteHumboldt Professor for AI and Computer Vision, University of WürzburgVerified email at uni-wuerzburg.de
