SS3D pretrains a feed-forward monocular 3D estimator via web-scale SfM self-supervision, achieving strong zero-shot cross-domain depth, ego-motion, and intrinsics prediction.
Semantic uncertainty measures answer disagreement rather than reliability, as valid answers vary and repeated errors appear certain; a bias-uncertainty decomposition separates variability from systematic error to improve evaluation.