Zhao jiang Liu

Sparse Annotation, Dense Supervision: Unleashing Self-Training Power for Occupancy Prediction With 2D Labels

Serving as a fundamental task in robotic navigation and autonomous driving, occupancy prediction is gaining increasing attention for its fine-grained perception of the 3D environment. Most existing methods rely on dense 3D annotations, which are expensive, labor-intensive, and difficult to scale in