AIM 2022 Challenge on Instagram Filter Removal: Methods and Results
Abstract
This paper introduces the methods and the results of AIM 2022 challenge on Instagram Filter Removal. Social media filters transform the images by consecutive non-linear operations, and the feature maps of the original content may be interpolated into a different domain. This reduces the overall performance of the recent deep learning strategies. The main goal of this challenge is to produce realistic and visually plausible images where the impact of the filters applied is mitigated while preserving the content. The proposed solutions are ranked in terms of the PSNR value with respect to the original images. There are two prior studies on this task as the baseline, and a total of 9 teams have competed in the final phase of the challenge. The comparison of qualitative results of the proposed solutions and the benchmark for the challenge are presented in this report.
Cite
Text
Kinli et al. "AIM 2022 Challenge on Instagram Filter Removal: Methods and Results." European Conference on Computer Vision Workshops, 2022. doi:10.1007/978-3-031-25066-8_2Markdown
[Kinli et al. "AIM 2022 Challenge on Instagram Filter Removal: Methods and Results." European Conference on Computer Vision Workshops, 2022.](https://mlanthology.org/eccvw/2022/kinli2022eccvw-aim/) doi:10.1007/978-3-031-25066-8_2BibTeX
@inproceedings{kinli2022eccvw-aim,
title = {{AIM 2022 Challenge on Instagram Filter Removal: Methods and Results}},
author = {Kinli, Furkan and Mentes, Sami and Özcan, Baris and Kiraç, Furkan and Timofte, Radu and Zuo, Yi and Wang, Zitao and Zhang, Xiaowen and Zhu, Yu and Li, Chenghua and Leng, Cong and Cheng, Jian and Liu, Shuai and Feng, Chaoyu and Bai, Furui and Wang, Xiaotao and Lei, Lei and Ma, Tianzhi and Gao, Zi-han and He, Wenxin and Yeo, Woon-Ha and Oh, Wang-Taek and Kim, Young-Il and Ryu, Han-Cheol and He, Gang and Long, Shaoyi and Sharif, S. M. A. and Naqvi, Rizwan Ali and Kim, Sungjun and Kim, Guisik and Lee, Seohyeon and Nathan, Sabari and Kansal, Priya},
booktitle = {European Conference on Computer Vision Workshops},
year = {2022},
pages = {27-43},
doi = {10.1007/978-3-031-25066-8_2},
url = {https://mlanthology.org/eccvw/2022/kinli2022eccvw-aim/}
}