Instance-level contrastive learning yields human brain-like representation without category-supervision

Humans learn object categories without millions of labels, but to date the models with the highest correspondence to primate visual systems are all category-supervised. This paper introduces a new self-supervised learning framework: instance-prototype contrastive learning (IPCL), and compares the internal representations learned by this model and other instance-level contrastive learning systems…

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