2026
Bridging the Depth Gap: Adaptive Scene-Instance Alignment for Training-Free Depth Refinement in Robotic Manipulation Scenes
RA-L 2026
Monocular depth estimation foundation models provide robust depth priors with exceptional generalization capabilities; however, their predictions typically lack a reliable metric scale and contain local inconsistencies in a zero-shot setting, which limit their deployment in unconstrained real-world