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

2022-08-23 20:32:38
Ren Yang, Radu Timofte, Xin Li, Qi Zhang, Lin Zhang, Fanglong Liu, Dongliang He, Fu li, He Zheng, Weihang Yuan, Pavel Ostyakov, Dmitry Vyal, Magauiya Zhussip, Xueyi Zou, Youliang Yan, Lei Li, Jingzhu Tang, Ming Chen, Shijie Zhao, Yu Zhu, Xiaoran Qin, Chenghua Li, Cong Leng, Jian Cheng, Claudio Rota, Marco Buzzelli, Simone Bianco, Raimondo Schettini, Dafeng Zhang, Feiyu Huang, Shizhuo Liu, Xiaobing Wang, Zhezhu Jin, Bingchen Li, Xin Li, Mingxi Li, Ding Liu, Wenbin Zou, Peijie Dong, Tian Ye, Yunchen Zhang, Ming Tan, Xin Niu, Mustafa Ayazoglu, Marcos Conde, Ui-Jin Choi, Zhuang Jia, Tianyu Xu, Yijian Zhang, Mao Ye, Dengyan Luo, Xiaofeng Pan, Liuhan Peng
arXiv_CV
       
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 this https URL. The homepage of this challenge is at this https URL.

Abstract (translated)

URL

https://arxiv.org/abs/2208.11184

PDF

https://arxiv.org/pdf/2208.11184.pdf

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