MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results
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| Formato: | Preprint |
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2024
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| author | Wu, Yaqi Fan, Zhihao Chu, Xiaofeng Ren, Jimmy S. Li, Xiaoming Yue, Zongsheng Li, Chongyi Zhou, Shangcheng Feng, Ruicheng Dai, Yuekun Yang, Peiqing Loy, Chen Change Xu, Senyan Sun, Zhijing Zhu, Jiaying Zhu, Yurui Fu, Xueyang Zha, Zheng-Jun Cao, Jun Li, Cheng Chen, Shu Ma, Liang Zhou, Shiyang Zeng, Haijin Feng, Kai Chen, Yongyong Su, Jingyong Guan, Xianyu Yu, Hongyuan Wan, Cheng Lin, Jiamin Han, Binnan Zou, Yajun Wu, Zhuoyuan Huang, Yuan Yu, Yongsheng Zhang, Daoan Li, Jizhe Yin, Xuanwu Zuo, Kunlong Lu, Yunfan Xu, Yijie Ma, Wenzong Guo, Weiyu Xiong, Hui Yu, Wei Luo, Bingchun Nathan, Sabari Kansal, Priya |
| author_facet | Wu, Yaqi Fan, Zhihao Chu, Xiaofeng Ren, Jimmy S. Li, Xiaoming Yue, Zongsheng Li, Chongyi Zhou, Shangcheng Feng, Ruicheng Dai, Yuekun Yang, Peiqing Loy, Chen Change Xu, Senyan Sun, Zhijing Zhu, Jiaying Zhu, Yurui Fu, Xueyang Zha, Zheng-Jun Cao, Jun Li, Cheng Chen, Shu Ma, Liang Zhou, Shiyang Zeng, Haijin Feng, Kai Chen, Yongyong Su, Jingyong Guan, Xianyu Yu, Hongyuan Wan, Cheng Lin, Jiamin Han, Binnan Zou, Yajun Wu, Zhuoyuan Huang, Yuan Yu, Yongsheng Zhang, Daoan Li, Jizhe Yin, Xuanwu Zuo, Kunlong Lu, Yunfan Xu, Yijie Ma, Wenzong Guo, Weiyu Xiong, Hui Yu, Wei Luo, Bingchun Nathan, Sabari Kansal, Priya |
| contents | The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems. However, the scarcity of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). Building on the achievements of the previous MIPI Workshops held at ECCV 2022 and CVPR 2023, we introduce our third MIPI challenge including three tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Nighttime Flare Removal track on MIPI 2024. In total, 170 participants were successfully registered, and 14 teams submitted results in the final testing phase. The developed solutions in this challenge achieved state-of-the-art performance on Nighttime Flare Removal. More details of this challenge and the link to the dataset can be found at https://mipi-challenge.org/MIPI2024/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_04867 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results Wu, Yaqi Fan, Zhihao Chu, Xiaofeng Ren, Jimmy S. Li, Xiaoming Yue, Zongsheng Li, Chongyi Zhou, Shangcheng Feng, Ruicheng Dai, Yuekun Yang, Peiqing Loy, Chen Change Xu, Senyan Sun, Zhijing Zhu, Jiaying Zhu, Yurui Fu, Xueyang Zha, Zheng-Jun Cao, Jun Li, Cheng Chen, Shu Ma, Liang Zhou, Shiyang Zeng, Haijin Feng, Kai Chen, Yongyong Su, Jingyong Guan, Xianyu Yu, Hongyuan Wan, Cheng Lin, Jiamin Han, Binnan Zou, Yajun Wu, Zhuoyuan Huang, Yuan Yu, Yongsheng Zhang, Daoan Li, Jizhe Yin, Xuanwu Zuo, Kunlong Lu, Yunfan Xu, Yijie Ma, Wenzong Guo, Weiyu Xiong, Hui Yu, Wei Luo, Bingchun Nathan, Sabari Kansal, Priya Image and Video Processing Computer Vision and Pattern Recognition The increasing demand for computational photography and imaging on mobile platforms has led to the widespread development and integration of advanced image sensors with novel algorithms in camera systems. However, the scarcity of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). Building on the achievements of the previous MIPI Workshops held at ECCV 2022 and CVPR 2023, we introduce our third MIPI challenge including three tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Nighttime Flare Removal track on MIPI 2024. In total, 170 participants were successfully registered, and 14 teams submitted results in the final testing phase. The developed solutions in this challenge achieved state-of-the-art performance on Nighttime Flare Removal. More details of this challenge and the link to the dataset can be found at https://mipi-challenge.org/MIPI2024/. |
| title | MIPI 2024 Challenge on Demosaic for HybridEVS Camera: Methods and Results |
| topic | Image and Video Processing Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2405.04867 |