NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution
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| Format: | Preprint |
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2025
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| author | Conde, Marcos V. Timofte, Radu Lu, Zihao Kong, Xiangyu Xing, Xiaoxia Wang, Fan Han, Suejin Park, MinKyu Zhang, Tianyu Luo, Xin Chen, Yeda Liu, Dong Pang, Li Yang, Yuhang Wang, Hongzhong Cao, Xiangyong Jiang, Ruixuan Xu, Senyan Jiang, Siyuan Fu, Xueyang Zha, Zheng-Jun Hao, Tianyu He, Yuhong Li, Ruoqi Yang, Yueqi Yu, Xiang Hong, Guanlan Yi, Minmin Chen, Yuanjia Zhang, Liwen Jin, Zijie Li, Cheng Liu, Lian Song, Wei Sun, Heng Wang, Yubo Wang, Jinghua Lu, Jiajie Ruangsan, Watchara |
| author_facet | Conde, Marcos V. Timofte, Radu Lu, Zihao Kong, Xiangyu Xing, Xiaoxia Wang, Fan Han, Suejin Park, MinKyu Zhang, Tianyu Luo, Xin Chen, Yeda Liu, Dong Pang, Li Yang, Yuhang Wang, Hongzhong Cao, Xiangyong Jiang, Ruixuan Xu, Senyan Jiang, Siyuan Fu, Xueyang Zha, Zheng-Jun Hao, Tianyu He, Yuhong Li, Ruoqi Yang, Yueqi Yu, Xiang Hong, Guanlan Yi, Minmin Chen, Yuanjia Zhang, Liwen Jin, Zijie Li, Cheng Liu, Lian Song, Wei Sun, Heng Wang, Yubo Wang, Jinghua Lu, Jiajie Ruangsan, Watchara |
| contents | This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. The goal of this challenge is two fold, (i) restore RAW images with blur and noise degradations, (ii) upscale RAW Bayer images by 2x, considering unknown noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. This report presents the current state-of-the-art in RAW Restoration. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2506_02197 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution Conde, Marcos V. Timofte, Radu Lu, Zihao Kong, Xiangyu Xing, Xiaoxia Wang, Fan Han, Suejin Park, MinKyu Zhang, Tianyu Luo, Xin Chen, Yeda Liu, Dong Pang, Li Yang, Yuhang Wang, Hongzhong Cao, Xiangyong Jiang, Ruixuan Xu, Senyan Jiang, Siyuan Fu, Xueyang Zha, Zheng-Jun Hao, Tianyu He, Yuhong Li, Ruoqi Yang, Yueqi Yu, Xiang Hong, Guanlan Yi, Minmin Chen, Yuanjia Zhang, Liwen Jin, Zijie Li, Cheng Liu, Lian Song, Wei Sun, Heng Wang, Yubo Wang, Jinghua Lu, Jiajie Ruangsan, Watchara Image and Video Processing Computer Vision and Pattern Recognition This paper reviews the NTIRE 2025 RAW Image Restoration and Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Restoration and Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. The goal of this challenge is two fold, (i) restore RAW images with blur and noise degradations, (ii) upscale RAW Bayer images by 2x, considering unknown noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. This report presents the current state-of-the-art in RAW Restoration. |
| title | NTIRE 2025 Challenge on RAW Image Restoration and Super-Resolution |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2506.02197 |