AI RESEARCH
SGR-OCC: Evolving Monocular Priors for Embodied 3D Occupancy Prediction via Soft-Gating Lifting and Semantic-Adaptive Geometric Refinement
arXiv CS.CV
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ArXi:2603.14076v1 Announce Type: new 3D semantic occupancy prediction is a cornerstone for embodied AI, enabling agents to perceive dense scene geometry and semantics incrementally from monocular video streams. However, current online frameworks face two critical bottlenecks: the inherent depth ambiguity of monocular estimation that causes "feature bleeding" at object boundaries, and the "cold start" instability where uninitialized temporal fusion layers distort high-quality spatial priors during early