May 16, 2024, 4:45 a.m. | Taha Emre, Arunava Chakravarty, Dmitrii Lachinov, Antoine Rivail, Ursula Schmidt-Erfurth, Hrvoje Bogunovi\'c

cs.CV updates on

arXiv:2405.09404v1 Announce Type: new
Abstract: Contrastive pretraining provides robust representations by ensuring their invariance to different image transformations while simultaneously preventing representational collapse. Equivariant contrastive learning, on the other hand, provides representations sensitive to specific image transformations while remaining invariant to others. By introducing equivariance to time-induced transformations, such as disease-related anatomical changes in longitudinal imaging, the model can effectively capture such changes in the representation space. In this work, we pro-pose a Time-equivariant Contrastive Learning (TC) method. First, an …

abstract arxiv disease image pretraining robust type while

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