Back to Search Start Over

AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results

Authors :
Yang, Ren
Timofte, Radu
Li, Xin
Zhang, Qi
Zhang, Lin
Liu, Fanglong
He, Dongliang
li, Fu
Zheng, He
Yuan, Weihang
Ostyakov, Pavel
Vyal, Dmitry
Zhussip, Magauiya
Zou, Xueyi
Yan, Youliang
Li, Lei
Tang, Jingzhu
Chen, Ming
Zhao, Shijie
Zhu, Yu
Qin, Xiaoran
Li, Chenghua
Leng, Cong
Cheng, Jian
Rota, Claudio
Buzzelli, Marco
Bianco, Simone
Schettini, Raimondo
Zhang, Dafeng
Huang, Feiyu
Liu, Shizhuo
Wang, Xiaobing
Jin, Zhezhu
Li, Bingchen
Li, Mingxi
Liu, Ding
Zou, Wenbin
Dong, Peijie
Ye, Tian
Zhang, Yunchen
Tan, Ming
Niu, Xin
Ayazoglu, Mustafa
Conde, Marcos
Choi, Ui-Jin
Jia, Zhuang
Xu, Tianyu
Zhang, Yijian
Ye, Mao
Luo, Dengyan
Pan, Xiaofeng
Peng, Liuhan
Publication Year :
2022

Abstract

This paper reviews the Challenge on Super-Resolution of Compressed Image and Video at AIM 2022. This challenge includes two tracks. Track 1 aims at the super-resolution of compressed image, and Track~2 targets the super-resolution of compressed video. In Track 1, we use the popular dataset DIV2K as the training, validation and test sets. In Track 2, we propose the LDV 3.0 dataset, which contains 365 videos, including the LDV 2.0 dataset (335 videos) and 30 additional videos. In this challenge, there are 12 teams and 2 teams that submitted the final results to Track 1 and Track 2, respectively. The proposed methods and solutions gauge the state-of-the-art of super-resolution on compressed image and video. The proposed LDV 3.0 dataset is available at https://github.com/RenYang-home/LDV_dataset. The homepage of this challenge is at https://github.com/RenYang-home/AIM22_CompressSR.<br />Comment: Camera-ready version

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2208.11184
Document Type :
Working Paper