Contrastive Learning with Stronger Augmentations
Contrastive Learning with Stronger Augmentations
Representation learning has significantly been developed with the advance of contrastive learning methods. Most of those methods are benefited from various data augmentations that are carefully designated to maintain their identities so that the images transformed from the same instance can still be retrieved. However, those carefully designed transformations limited …