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.
@article{arxiv.2208.11184,
title = {AIM 2022 Challenge on Super-Resolution of Compressed Image and Video: Dataset, Methods and Results},
author = {Ren Yang and Radu Timofte and Xin Li and Qi Zhang and Lin Zhang and Fanglong Liu and Dongliang He and Fu li and He Zheng and Weihang Yuan and Pavel Ostyakov and Dmitry Vyal and Magauiya Zhussip and Xueyi Zou and Youliang Yan and Lei Li and Jingzhu Tang and Ming Chen and Shijie Zhao and Yu Zhu and Xiaoran Qin and Chenghua Li and Cong Leng and Jian Cheng and Claudio Rota and Marco Buzzelli and Simone Bianco and Raimondo Schettini and Dafeng Zhang and Feiyu Huang and Shizhuo Liu and Xiaobing Wang and Zhezhu Jin and Bingchen Li and Xin Li and Mingxi Li and Ding Liu and Wenbin Zou and Peijie Dong and Tian Ye and Yunchen Zhang and Ming Tan and Xin Niu and Mustafa Ayazoglu and Marcos Conde and Ui-Jin Choi and Zhuang Jia and Tianyu Xu and Yijian Zhang and Mao Ye and Dengyan Luo and Xiaofeng Pan and Liuhan Peng},
journal= {arXiv preprint arXiv:2208.11184},
year = {2022}
}