Abstract:Generalizing learned representations across significantly different visual domains is a fundamental yet crucial ability of the human visual system. While recent selfsupervised learning methods have achieved good performances with evaluation set on the same domain as the training set, they will have an undesirable performance decrease when tested on a different domain. Therefore, the selfsupervised learning from multiple domains task is proposed to learn domain-invariant features that are not only suitable for … Show more
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