Re-Depth Anything: Enhancing Depth Perception with Self-Supervised Re-lighting

This ArXiv paper introduces a novel approach to refining depth estimation using self-supervised learning techniques and re-lighting strategies. The core contribution likely involves improving the accuracy and robustness of existing depth models during the testing phase.