On compositions of transformations in contrastive self-supervised learning
In the image domain, excellent representations can be learned by inducing invariance to content-preserving transformations via noise contrastive learning. In this paper, we generalize contrastive learning to a wider set of transformations, and their compositions, for which either invariance or disti...
| Автори: | , , , , , , |
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| Формат: | Conference item |
| Мова: | English |
| Опубліковано: |
IEEE
2022
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