Towards Domain-Agnostic Contrastive Learning

Kenji Kawaguchi
Kenji Kawaguchi
Hieu Pham
Hieu Pham
Cited by: 0|Bibtex|Views22|Links

Abstract:

Despite recent success, most contrastive self-supervised learning methods are domain-specific, relying heavily on data augmentation techniques that require knowledge about a particular domain, such as image cropping and rotation. To overcome such limitation, we propose a novel domain-agnostic approach to contrastive learning, named DACL...More

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