AI RESEARCH
Con-DSO: Learning Short-Horizon Consistency Priors for RGB-D Direct Sparse Odometry
arXiv CS.CV
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ArXi:2605.27952v1 Announce Type: new 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 alignment.