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[bibtex]@InProceedings{Li_2022_CVPR, author = {Li, Yawei and Zhang, Kai and Timofte, Radu and Van Gool, Luc and Kong, Fangyuan and Li, Mingxi and Liu, Songwei and Du, Zongcai and Liu, Ding and Zhou, Chenhui and Chen, Jingyi and Han, Qingrui and Li, Zheyuan and Liu, Yingqi and Chen, Xiangyu and Cai, Haoming and Qiao, Yu and Dong, Chao and Sun, Long and Pan, Jinshan and Zhu, Yi and Zong, Zhikai and Liu, Xiaoxiao and Hui, Zheng and Yang, Tao and Ren, Peiran and Xie, Xuansong and Hua, Xian-Sheng and Wang, Yanbo and Ji, Xiaozhong and Lin, Chuming and Luo, Donghao and Tai, Ying and Wang, Chengjie and Zhang, Zhizhong and Xie, Yuan and Cheng, Shen and Luo, Ziwei and Yu, Lei and Wen, Zhihong and Wu, Qi and Li, Youwei and Fan, Haoqiang and Sun, Jian and Liu, Shuaicheng and Huang, Yuanfei and Jin, Meiguang and Huang, Hua and Liu, Jing and Zhang, Xinjian and Wang, Yan and Long, Lingshun and Li, Gen and Zhang, Yuanfan and Cao, Zuowei and Sun, Lei and Alexander, Panaetov and Wang, Yucong and Cai, Minjie and Wang, Li and Tian, Lu and Wang, Zheyuan and Ma, Hongbing and Liu, Jie and Chen, Chao and Cai, Yidong and Tang, Jie and Wu, Gangshan and Wang, Weiran and Huang, Shirui and Lu, Honglei and Liu, Huan and Wang, Keyan and Chen, Jun and Chen, Shi and Miao, Yuchun and Huang, Zimo and Zhang, Lefei and Ayazo\u{g}lu, Mustafa and Xiong, Wei and Xiong, Chengyi and Wang, Fei and Li, Hao and Wen, Ruimian and Yang, Zhijing and Zou, Wenbin and Zheng, Weixin and Ye, Tian and Zhang, Yuncheng and Kong, Xiangzhen and Arora, Aditya and Zamir, Syed Waqas and Khan, Salman and Hayat, Munawar and Khan, Fahad Shahbaz and Gao, Dandan and Zhou, Dengwen and Zhou, Dengwen and Ning, Qian and Tang, Jingzhu and Huang, Han and Wang, Yufei and Peng, Zhangheng and Li, Haobo and Guan, Wenxue and Gong, Shenghua and Li, Xin and Liu, Jun and Wang, Wanjun and Zeng, Kun and Lin, Hanjiang and Chen, Xinyu and Fang, Jinsheng}, title = {NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results}, booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops}, month = {June}, year = {2022}, pages = {1062-1102} }
NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results
Abstract
This paper reviews the NTIRE 2022 challenge on efficient single image super-resolution with focus on the proposed solutions and results. The task of the challenge was to super-resolve an input image with a magnification factor of 4 based on pairs of low and corresponding high resolution images. The aim was to design a network for single image super-resolution that achieved improvement of efficiency measured according to several metrics including runtime, parameters, FLOPs, activations, and memory consumption while at least maintaining the PSNR of 29.00dB on DIV2K validation set. IMDN is set as the baseline for efficiency measurement. The challenge had 3 tracks including the main track (runtime), sub-track one (model complexity), and sub-track two (overall performance). In the main track, the practical runtime performance of the submissions was evaluated. The rank of the teams were determined directly by the absolute value of the average runtime on the validation set and test set. In sub-track one, the number of parameters and FLOPs were considered. And the individual rankings of the two metrics were summed up to determine a final ranking in this track. In sub-track two, all of the five metrics mentioned in the description of the challenge including runtime, parameter count, FLOPs, activations, and memory consumption were considered. Similar to sub-track one, the rankings of five metrics were summed up to determine a final ranking. The challenge had 303 registered participants, and 43 teams made valid submissions. They gauge the state-of-the-art in efficient single image super-resolution.
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