Unsupervised Monocular Road Segmentation for Autonomous Driving via Scene Geometry

ArXi:2510.16790v2 Announce Type: replace This paper presents a fully unsupervised approach for binary road segmentation (road vs. non-road), eliminating the reliance on costly manually labeled datasets. The method leverages scene geometry and temporal cues to distinguish road from non-road regions. Weak labels are first generated from geometric priors, marking pixels above the horizon as non-road and a predefined quadrilateral in front of the vehicle as road.