| 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 | 436 | 2019 |
| Overcoming catastrophic forgetting in incremental few-shot learning by finding flat minima G Shi, J Chen, W Zhang, LM Zhan, XM Wu Advances in neural information processing systems 34, 6747-6761, 2021 | 175 | 2021 |
| NTIRE 2023 challenge on stereo image super-resolution: Methods and results L Wang, Y Guo, Y Wang, J Li, S Gu, R Timofte, M Cheng, H Ma, Q Ma, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 79 | 2023 |
| Hat: Hybrid attention transformer for image restoration X Chen, X Wang, W Zhang, X Kong, Y Qiao, J Zhou, C Dong arXiv preprint arXiv:2309.05239, 2023 | 56 | 2023 |
| DVMSR: Distillated Vision Mamba for Efficient Super-Resolution X Lei, W Zhang*, W Cao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 41* | 2024 |
| Recon: Reducing conflicting gradients from the root for multi-task learning G Shi, Q Li, W Zhang, J Chen, XM Wu The Eleventh International Conference on Learning Representations, 2023 | 41 | 2023 |
| RankSRGAN: Super Resolution Generative Adversarial Networks with Learning to Rank W Zhang, Y Liu, C Dong, Y Qiao IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021 | 41 | 2021 |
| A closer look at blind super-resolution: Degradation models, baselines, and performance upper bounds W Zhang, G Shi, Y Liu, C Dong, XM Wu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 32 | 2022 |
| Real-world image super-resolution as multi-task learning W Zhang, X Li, G Shi, X Chen, Y Qiao, X Zhang, XM Wu, C Dong Advances in Neural Information Processing Systems 36, 21003-21022, 2023 | 26 | 2023 |
| Spatial resolution enhancement of satellite microwave radiometer data with deep residual convolutional neural network W Hu, Y Li, W Zhang, S Chen, X Lv, L Ligthart Remote Sensing 11 (7), 771, 2019 | 23 | 2019 |
| A deconvolution technology of microwave radiometer data using convolutional neural networks W Hu, W Zhang*, S Chen, X Lv, D An, L Ligthart Remote Sensing 10 (2), 275, 2018 | 19 | 2018 |
| Spatial resolution matching of microwave radiometer data with convolutional neural network Y Li, W Hu, S Chen, W Zhang, R Guo, J He, L Ligthart Remote Sensing 11 (20), 2432, 2019 | 17 | 2019 |
| Radar cross section near-field to far-field prediction for isotropic-point scattering target based on regression estimation Y Liu, W Hu, W Zhang, J Sun, B Xing, L Ligthart Sensors 20 (21), 6023, 2020 | 10 | 2020 |
| SEAL: A Framework for Systematic Evaluation of Real-World Super-Resolution W Zhang, X Li, X Chen, Y Qiao, XM Wu, C Dong The Twelfth International Conference on Learning Representations. Spotlight, 2023 | 8 | 2023 |
| UniFashion: A Unified Vision-Language Model for Multimodal Fashion Retrieval and Generation X Zhao, Y Zhang, W Zhang, XM Wu Empirical Methods in Natural Language Processing, 2024 | 6 | 2024 |
| Generalizing Weather Forecast to Fine-grained Temporal Scales via Physics-AI Hybrid Modeling W Xu, F Ling, W Zhang, T Han, H Chen, W Ouyang, L Bai Advances in Neural Information Processing Systems, 2024 | 5 | 2024 |
| GRIDS: Grouped Multiple-Degradation Restoration with Image Degradation Similarity S Cao, Y Liu, W Zhang, Y Qiao, C Dong European Conference on Computer Vision., 2024 | 4 | 2024 |
| Learning A Low-Level Vision Generalist via Visual Task Prompt X Chen, Y Liu, Y Pu, W Zhang, J Zhou, Y Qiao, C Dong ACM international conference on multimedia, 2024 | 3 | 2024 |
| Understanding Layer Significance in LLM Alignment G Shi, Z Lu, X Dong, W Zhang, X Zhang, Y Feng, XM Wu arXiv preprint arXiv:2410.17875, 2024 | 2 | 2024 |
| Postcast: Generalizable postprocessing for precipitation nowcasting via unsupervised blurriness modeling J Gong, S Tu, W Yang, B Fei, K Chen, W Zhang, X Yang, W Ouyang, L Bai International Conference on Learning Representations, 2024 | 2 | 2024 |
Chao DongShenzhen Institutes of Advanced Technology, Chinese Academy of SciencesPreverjeni e-poštni naslov na siat.ac.cn
