Delving into Inter-Image Invariance for Unsupervised Visual Representations. (arXiv:2008.11702v3 [cs.CV] UPDATED)

Contrastive learning has recently shown immense potential in unsupervised
visual representation learning. Existing studies in this track mainly focus on
intra-image invariance learning. The learning typically uses rich intra-image
transformations to construct positive pairs and then maximizes agreement using
a contrastive loss. The merits of inter-image invariance, conversely, remain
much less explored. One major obstacle to exploit inter-image invariance is
that it is unclear how to reliably construct inter-image positive pairs, and
further derive effective supervision from them since no …

arxiv image unsupervised