arxivcs.CVcs.LG2026-07-01
Mirror-Fusion Attention for Reflection-Aware Self-Supervised Representation Learning
Ruixin Li, Jin Liu, Yuling Shi, Stefano Lodi
Most self-supervised learning (SSL) methods encourage invariance across augmentations, but strict flip invariance can suppress informative left--right correspondences in approximately bilateral data such as medical images and human faces. We propose Mirror-Fusion-Augmented Self-S…