DenseTRF: Texture-Aware Unsupervised Representation Adaptation for Surgical Scene Dense Prediction
This work proposes DenseTRF, a self-supervised representation adaptation framework based on texture-centric attention that leverages slot attention to learn texture-aware representations that capture invariant visual structures and significantly improves robustness to domain shifts.