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.

翻译：2021年图像相似性挑战引入了一套数据集,作为评估最近图像复制检测方法的新基准。有200名参赛者参加竞争。本文对上层提交材料进行了定量和定性分析。看起来,最困难的图像转换要么涉及严重图像作物,要么隐藏在与本地像素扰动无关的图像中。获胜的提交材料的关键算法要素是:强力增强、自我监督学习、分数正常化、明确重叠检测和全球描述匹配培训,然后是配对图像比较。