Corpus ID: 211096730

A Simple Framework for Contrastive Learning of Visual Representations

@article{Chen2020ASF,
  title={A Simple Framework for Contrastive Learning of Visual Representations},
  author={Ting Chen and Simon Kornblith and Mohammad Norouzi and Geoffrey E. Hinton},
  journal={ArXiv},
  year={2020},
  volume={abs/2002.05709}
}
This paper presents SimCLR: a simple framework for contrastive learning of visual representations. We simplify recently proposed contrastive self-supervised learning algorithms without requiring specialized architectures or a memory bank. In order to understand what enables the contrastive prediction tasks to learn useful representations, we systematically study the major components of our framework. We show that (1) composition of data augmentations plays a critical role in defining effective… Expand
1,390 Citations
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