Results and findings of the 2021 Image Similarity Challenge

• URL: http://arxiv.org/abs/2202.04007v1
• Date: Tue, 8 Feb 2022 17:23:32 GMT
• Title: Results and findings of the 2021 Image Similarity Challenge
• Authors: Zo\"e Papakipos, Giorgos Tolias, Tomas Jenicek, Ed Pizzi, Shuhei Yokoo, Wenhao Wang, Yifan Sun, Weipu Zhang, Yi Yang, Sanjay Addicam, Sergio Manuel Papadakis, Cristian Canton Ferrer, Ondrej Chum, Matthijs Douze
• Abstract summary: The 2021 Image Similarity Challenge introduced a dataset to serve as a new benchmark to evaluate recent image copy detection methods. This paper presents a quantitative and qualitative analysis of the top submissions.
• Score: 43.79331237080075
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The 2021 Image Similarity Challenge introduced a dataset to serve as a new benchmark to evaluate recent image copy detection methods. There were 200 participants to the competition. This paper presents a quantitative and qualitative analysis of the top submissions. It appears that the most difficult image transformations involve either severe image crops or hiding into unrelated images, combined with local pixel perturbations. The key algorithmic elements in the winning submissions are: training on strong augmentations, self-supervised learning, score normalization, explicit overlay detection, and global descriptor matching followed by pairwise image comparison.

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