AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results

This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution image...

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Published in:arXiv.org 2020-09
Main Authors: Zhang, Kai, Danelljan, Martin, Li, Yawei, Timofte, Radu, Liu, Jie, Tang, Jie, Wu, Gangshan, Zhu, Yu, He, Xiangyu, Xu, Wenjie, Li, Chenghua, Leng, Cong, Cheng, Jian, Wu, Guangyang, Wang, Wenyi, Liu, Xiaohong, Zhao, Hengyuan, Kong, Xiangtao, He, Jingwen, Yu, Qiao, Chao, Dong, Luo, Xiaotong, Chen, Liang, Zhang, Jiangtao, Maitreya Suin, Purohit, Kuldeep, Rajagopalan, A N, Li, Xiaochuan, Lang, Zhiqiang, Nie, Jiangtao, Wei, Wei, Zhang, Lei, Muqeet, Abdul, Hwang, Jiwon, Yang, Subin, Kang, JungHeum, Sung-Ho, Bae, Kim, Yongwoo, Qu, Yanyun, Geun-Woo Jeon, Jun-Ho, Choi, Jun-Hyuk, Kim, Jong-Seok, Lee, Marty, Steven, Marty, Eric, Xiong, Dongliang, Chen, Siang, Zha, Lin, Jiang, Jiande, Gao, Xinbo, Lu, Wen, Wang, Haicheng, Vineeth Bhaskara, Levinshtein, Alex, Tsogkas, Stavros, Jepson, Allan, Kong, Xiangzhen, Zhao, Tongtong, Zhao, Shanshan, Hrishikesh, P S, Densen Puthussery, Jiji, C V, Nan, Nan, Liu, Shuai, Cai, Jie, Meng, Zibo, Ding, Jiaming, Chiu, Man Ho, Wang, Xuehui, Yan, Qiong, Zhao, Yuzhi, Long, Chen, Long, Sun, Wang, Wenhao, Liu, Zhenbing, Rushi Lan, Rao, Muhammad Umer, Micheloni, Christian
Format: Article
Language:English
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Image resolution
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Summary:This paper reviews the AIM 2020 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The challenge task was to super-resolve an input image with a magnification factor x4 based on a set of prior examples of low and corresponding high resolution images. The goal is to devise a network that reduces one or several aspects such as runtime, parameter count, FLOPs, activations, and memory consumption while at least maintaining PSNR of MSRResNet. The track had 150 registered participants, and 25 teams submitted the final results. They gauge the state-of-the-art in efficient single image super-resolution.
ISSN:2331-8422