AI RESEARCH
GHOST: Ground-projected Hypotheses from Observed Structure-from-Motion Trajectories
arXiv CS.CV
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ArXi:2603.20583v1 Announce Type: cross We present a scalable self-supervised approach for segmenting feasible vehicle trajectories from monocular images for autonomous driving in complex urban environments. Leveraging large-scale dashcam videos, we treat recorded ego-vehicle motion as implicit supervision and recover camera trajectories via monocular structure-from-motion, projecting them onto the ground plane to generate spatial masks of traversed regions without manual annotation.