| Image super-resolution using deep convolutional networks C Dong, CC Loy, K He, X Tang IEEE transactions on pattern analysis and machine intelligence 38 (2), 295-307, 2015 | 9611 | 2015 |
| Learning a deep convolutional network for image super-resolution C Dong, CC Loy, K He, X Tang Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 6119 | 2014 |
| Esrgan: Enhanced super-resolution generative adversarial networks X Wang, K Yu, S Wu, J Gu, Y Liu, C Dong, Y Qiao, C Change Loy Proceedings of the European conference on computer vision (ECCV) workshops, 0-0, 2018 | 4231 | 2018 |
| Accelerating the super-resolution convolutional neural network C Dong, CC Loy, X Tang Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 3648 | 2016 |
| Ntire 2017 challenge on single image super-resolution: Methods and results R Timofte, E Agustsson, L Van Gool, MH Yang, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 1696 | 2017 |
| Edvr: Video restoration with enhanced deformable convolutional networks X Wang, KCK Chan, K Yu, C Dong, C Change Loy Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 1078 | 2019 |
| Recovering realistic texture in image super-resolution by deep spatial feature transform X Wang, K Yu, C Dong, CC Loy Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 1070 | 2018 |
| Compression artifacts reduction by a deep convolutional network C Dong, Y Deng, CC Loy, X Tang Proceedings of the IEEE international conference on computer vision, 576-584, 2015 | 937 | 2015 |
| Real-esrgan: Training real-world blind super-resolution with pure synthetic data X Wang, L Xie, C Dong, Y Shan Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 912 | 2021 |
| Unsupervised image super-resolution using cycle-in-cycle generative adversarial networks Y Yuan, S Liu, J Zhang, Y Zhang, C Dong, L Lin Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 754 | 2018 |
| Blind super-resolution with iterative kernel correction J Gu, H Lu, W Zuo, C Dong Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 536 | 2019 |
| Basicvsr: The search for essential components in video super-resolution and beyond KCK Chan, X Wang, K Yu, C Dong, CC Loy Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2021 | 436 | 2021 |
| Ranksrgan: Generative adversarial networks with ranker for image super-resolution W Zhang, Y Liu, C Dong, Y Qiao Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 376 | 2019 |
| Efficient image super-resolution using pixel attention H Zhao, X Kong, J He, Y Qiao, C Dong Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2020 | 324 | 2020 |
| Multiple cycle-in-cycle generative adversarial networks for unsupervised image super-resolution Y Zhang, S Liu, C Dong, X Zhang, Y Yuan IEEE transactions on Image Processing 29, 1101-1112, 2019 | 248 | 2019 |
| Beautygan: Instance-level facial makeup transfer with deep generative adversarial network T Li, R Qian, C Dong, S Liu, Q Yan, W Zhu, L Lin Proceedings of the 26th ACM international conference on Multimedia, 645-653, 2018 | 244 | 2018 |
| Crafting a toolchain for image restoration by deep reinforcement learning K Yu, C Dong, L Lin, CC Loy Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 212 | 2018 |
| Video super-resolution based on deep learning: a comprehensive survey H Liu, Z Ruan, P Zhao, C Dong, F Shang, Y Liu, L Yang, R Timofte Artificial Intelligence Review 55 (8), 5981-6035, 2022 | 172 | 2022 |
| Interpreting super-resolution networks with local attribution maps J Gu, C Dong Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 167 | 2021 |
| Understanding deformable alignment in video super-resolution KCK Chan, X Wang, K Yu, C Dong, CC Loy Proceedings of the AAAI conference on artificial intelligence 35 (2), 973-981, 2021 | 152 | 2021 |
Yu QiaoProfessor of Shanghai AI Laboratory; Shenzhen Institutes of Advanced Technology, CAS在 siat.ac.cn 的电子邮件经过验证
