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

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
Qiao, Yu
Dong, Chao
Luo, Xiaotong
Chen, Liang
Zhang, Jiangtao
Suin, Maitreya
Purohit, Kuldeep
Rajagopalan, A. N.
Li, Xiaochuan
Lang, Zhiqiang
Nie, Jiangtao
Wei, Wei
Zhang, Lei
Muqeet, Abdul
Hwang, Jiwon
Yang, Subin
Kang, JungHeum
Bae, Sung-Ho
Kim, Yongwoo
Qu, Yanyun
Jeon, Geun-Woo
Choi, Jun-Ho
Kim, Jun-Hyuk
Lee, Jong-Seok
Marty, Steven
Marty, Eric
Xiong, Dongliang
Chen, Siang
Zha, Lin
Jiang, Jiande
Gao, Xinbo
Lu, Wen
Wang, Haicheng
Bhaskara, Vineeth
Levinshtein, Alex
Tsogkas, Stavros
Jepson, Allan
Kong, Xiangzhen
Zhao, Tongtong
Zhao, Shanshan
S, Hrishikesh P
Puthussery, Densen
C V, Jiji
Nan, Nan
Liu, Shuai
Cai, Jie
Meng, Zibo
Ding, Jiaming
Ho, Chiu Man
Wang, Xuehui
Yan, Qiong
Zhao, Yuzhi
Chen, Long
Sun, Long
Wang, Wenhao
Liu, Zhenbing
Lan, Rushi
Umer, Rao Muhammad
Micheloni, Christian
Publication Year :
2020

Abstract

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.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2009.06943
Document Type :
Working Paper