Con-DSO: Learning Short-Horizon Consistency Priors for RGB-D Direct Sparse Odometry 事件

Con-DSO: Learning Short-Horizon Consistency Priors for RGB-D Direct Sparse Odometry arXiv:2605.27952v1 Announce Type: new Abstract: Visual odometry (VO) is a fundamental component in robotics and augmented reality. RGB-D direct VO benefits from metric depth measurements, but it can degrade in challenging environments, where dynamic objects, occlusions, illumination changes, and unreliable depth violate the short-horizon photometric and depth-geometric consistency assumptions used by direct alig