Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey
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arXiv
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| Format: | Preprint |
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2024
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| author | Conde, Marcos V. Vasluianu, Florin-Alexandru Timofte, Radu Zhang, Jianxing Li, Jia Wang, Fan Li, Xiaopeng Liu, Zikun Park, Hyunhee Song, Sejun Kim, Changho Huang, Zhijuan Yu, Hongyuan Wan, Cheng Xiang, Wending Lin, Jiamin Zhong, Hang Zhang, Qiaosong Sun, Yue Yin, Xuanwu Zuo, Kunlong Xu, Senyan Jiang, Siyuan Sun, Zhijing Zhu, Jiaying Li, Liangyan Chen, Ke Li, Yunzhe Ning, Yimo Zhao, Guanhua Chen, Jun Yu, Jinyang Xu, Kele Xu, Qisheng Dou, Yong |
| author_facet | Conde, Marcos V. Vasluianu, Florin-Alexandru Timofte, Radu Zhang, Jianxing Li, Jia Wang, Fan Li, Xiaopeng Liu, Zikun Park, Hyunhee Song, Sejun Kim, Changho Huang, Zhijuan Yu, Hongyuan Wan, Cheng Xiang, Wending Lin, Jiamin Zhong, Hang Zhang, Qiaosong Sun, Yue Yin, Xuanwu Zuo, Kunlong Xu, Senyan Jiang, Siyuan Sun, Zhijing Zhu, Jiaying Li, Liangyan Chen, Ke Li, Yunzhe Ning, Yimo Zhao, Guanhua Chen, Jun Yu, Jinyang Xu, Kele Xu, Qisheng Dou, Yong |
| contents | This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge is to upscale RAW Bayer images by 2x, considering unknown degradations such as noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. The performance of the top-5 submissions is reviewed and provided here as a gauge for the current state-of-the-art in RAW Image Super-Resolution. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2404_16223 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey Conde, Marcos V. Vasluianu, Florin-Alexandru Timofte, Radu Zhang, Jianxing Li, Jia Wang, Fan Li, Xiaopeng Liu, Zikun Park, Hyunhee Song, Sejun Kim, Changho Huang, Zhijuan Yu, Hongyuan Wan, Cheng Xiang, Wending Lin, Jiamin Zhong, Hang Zhang, Qiaosong Sun, Yue Yin, Xuanwu Zuo, Kunlong Xu, Senyan Jiang, Siyuan Sun, Zhijing Zhu, Jiaying Li, Liangyan Chen, Ke Li, Yunzhe Ning, Yimo Zhao, Guanhua Chen, Jun Yu, Jinyang Xu, Kele Xu, Qisheng Dou, Yong Computer Vision and Pattern Recognition Image and Video Processing This paper reviews the NTIRE 2024 RAW Image Super-Resolution Challenge, highlighting the proposed solutions and results. New methods for RAW Super-Resolution could be essential in modern Image Signal Processing (ISP) pipelines, however, this problem is not as explored as in the RGB domain. Th goal of this challenge is to upscale RAW Bayer images by 2x, considering unknown degradations such as noise and blur. In the challenge, a total of 230 participants registered, and 45 submitted results during thee challenge period. The performance of the top-5 submissions is reviewed and provided here as a gauge for the current state-of-the-art in RAW Image Super-Resolution. |
| title | Deep RAW Image Super-Resolution. A NTIRE 2024 Challenge Survey |
| topic | Computer Vision and Pattern Recognition Image and Video Processing |
| url | https://arxiv.org/abs/2404.16223 |