AIM 2022 Challenge on Instagram Filter Removal: Methods and Results
This addresses the issue of social media filters degrading image quality for AI applications, but it is incremental as it builds on prior studies and focuses on a specific domain.
The paper tackles the problem of removing Instagram filters from images to improve deep learning performance, reporting results from a 2022 challenge where 9 teams competed and were ranked based on PSNR values.
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.