Variance Fingerprints: Component-Wise Identification of Content Factors by Augmentation Design

Augmentation-based self-supervised learning can recover the content shared across views without separating its underlying factors into individual coordinates. We ask whether augmentations can be designed to make those factors identifiable. Our approach allows content factors to fluctuate across augm