NTIRE 2022 Challenge on Efficient Super-Resolution: Methods and Results

被引:30
作者
Li, Yawei [1 ]
Zhang, Kai [1 ]
Timofte, Radu [1 ,2 ]
Van Gool, Luc [1 ]
Kong, Fangyuan
Li, Mingxi
Liu, Songwei
Du, Zongcai [3 ]
Liu, Ding [4 ]
Zhou, Chenhui [5 ]
Chen, Jingyi [5 ]
Han, Qingrui [5 ]
Li, Zheyuan [6 ]
Liu, Yingqi [6 ]
Chen, Xiangyu [6 ,7 ]
Cai, Haoming [6 ]
Qiao, Yu [6 ,8 ]
Dong, Chao [6 ]
Sun, Long [9 ]
Pan, Jinshan [9 ]
Zhu, Yi [10 ]
Zong, Zhikai [11 ]
Liu, Xiaoxiao [11 ]
Hui, Zheng [12 ]
Yang, Tao [12 ]
Ren, Peiran [12 ]
Xie, Xuansong [12 ]
Hua, Xian-Sheng [12 ]
Wang, Yanbo
Ji, Xiaozhong [13 ,14 ]
Lin, Chuming [14 ]
Luo, Donghao [14 ]
Tai, Ying [14 ]
Wang, Chengjie [14 ]
Zhang, Zhizhong [13 ]
Xie, Yuan [13 ]
Cheng, Shen [15 ]
Luo, Ziwei [15 ]
Yu, Lei [15 ]
Wen, Zhihong [15 ]
Wul, Qi [15 ]
Li, Youwei [15 ]
Fan, Haoqiang [15 ]
Sun, Jian [15 ]
Liu, Shuaicheng [15 ,16 ]
Huang, Yuanfei [17 ]
Jin, Meiguang [18 ]
Huang, Hua [17 ]
Liu, Jing [19 ]
Zhang, Xinjian [19 ]
机构
[1] Swiss Fed Inst Technol, Comp Vis Lab, Zurich, Switzerland
[2] Univ Wurzburg, Wurzburg, Germany
[3] Nanjing Univ, State Key Lab Novel Software Technol, Nanjing, Peoples R China
[4] ByteDance Inc, Beijing, Peoples R China
[5] NetEase Inc, Hangzhou, Peoples R China
[6] Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Peoples R China
[7] Univ Macau, Macau, Peoples R China
[8] Shanghai AI Lab, Shanghai, Peoples R China
[9] Nanjing Univ Sci & Technol, Nanjing, Peoples R China
[10] Amazon Web Serv, Seattle, WA USA
[11] Qingdao Hiimage Technol Co Ltd, Qingdao, Peoples R China
[12] EFC, Alibaba DAMO Acad, Hangzhou, Zhejiang, Peoples R China
[13] East China Normal Univ, Shanghai, Peoples R China
[14] Tencent, Youtu Lab, Shanghai, Peoples R China
[15] Megvii Technol, Beijing, Peoples R China
[16] Univ Elect Sci & Technol China, Chengdu, Peoples R China
[17] Beijing Normal Univ, Sch Artificial Intelligence, Beijing, Peoples R China
[18] Alibaba Grp, Hangzhou, Peoples R China
[19] Bilibili AI, Beijing, Peoples R China
[20] Nankai Univ, Nankai Baidu Joint Lab, Tianjin, Peoples R China
[21] Tencent Online Video, Platform Technol, Shanghai, Peoples R China
[22] Higher Sch Econ, St Petersburg, Russia
[23] Huawei Moscow Res Ctr, Moscow, Russia
[24] Hunan Univ, Changsha, Peoples R China
[25] Xidian Univ, Xian, Peoples R China
[26] Xilinx Technol Beijing Ltd, Beijing, Peoples R China
[27] Xinjiang Univ, Coll Informat Sci & Engn, Urumqi, Peoples R China
[28] Tsinghua Univ, Dept Elect Engn, Beijing, Peoples R China
[29] Nanjing Univ, Nanjing, Peoples R China
[30] Xidian Univ, Sch Telecommun Engn, Xian, Peoples R China
[31] Wuhan Univ, Sch Comp Sci, Wuhan, Peoples R China
[32] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu, Peoples R China
[33] Univ Sydney, Sch Comp Sci, Sydney, NSW, Australia
[34] Aselsan Res, Ankara, Turkey
[35] South Cent Univ Nationalities, Sch Elect & Informat Engn, Wuhan, Peoples R China
[36] Guangdong Univ Technol, Guangzhou, Peoples R China
[37] Incept Inst Artificial Intelligence IIAI, Abu Dhabi, U Arab Emirates
[38] Monash Univ, Melbourne, Vic, Australia
[39] Mohamed Bin Zayed Univ AI, Abu Dhabi, U Arab Emirates
[40] North China Elect Power Univ, Beijing, Peoples R China
[41] Xidian Univ, Sch Artificial Intelligence, Xian, Peoples R China
[42] Jilin Univ, Coll Comp Sci & Technol, Changchun, Peoples R China
[43] Beihang Univ, Sch Elect & Informat Engn, Beijing, Peoples R China
[44] North China Elect Power Univ, Sch Control & Comp Engn, Beijing, Peoples R China
[45] Minnan Normal Univ, Zhangzhou, Fujian, Peoples R China
[46] Minjiang Univ, Fuzhou, Fujian, Peoples R China
[47] Space Applicat Ctr, Ahmadabad, Gujarat, India
[48] Natl Taiwan Univ, Dept Elect Engn, Taipei, Taiwan
[49] Natl Taiwan Univ, Grad Inst Elect Engn, Taipei, Taiwan
[50] Alibaba Grp, DAMO Acad, Shanghai, Peoples R China
来源
2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, CVPRW 2022 | 2022年
关键词
IMAGE SUPERRESOLUTION;
D O I
10.1109/CVPRW56347.2022.00118
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
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 x4 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.
引用
收藏
页码:1061 / 1101
页数:41
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