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Interventional Contrastive Learning with Meta Semantic Regularizer. (arXiv:2206.14702v1 [cs.CV])
June 30, 2022, 1:12 a.m. | Wenwen Qiang, Jiangmeng Li, Changwen Zheng, Bing Su, Hui Xiong
cs.CV updates on arXiv.org arxiv.org
Contrastive learning (CL)-based self-supervised learning models learn visual
representations in a pairwise manner. Although the prevailing CL model has
achieved great progress, in this paper, we uncover an ever-overlooked
phenomenon: When the CL model is trained with full images, the performance
tested in full images is better than that in foreground areas; when the CL
model is trained with foreground areas, the performance tested in full images
is worse than that in foreground areas. This observation reveals that
backgrounds in …
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