AI RESEARCH
WeatherOcc3D: VLM-Assisted Adverse Weather Aware 3D Semantic Occupancy Prediction
arXiv CS.CV
•
ArXi:2605.16127v1 Announce Type: new While multi-modal 3D semantic occupancy prediction typically enhances robustness by fusing camera and LiDAR inputs, its effectiveness is fundamentally constrained by environmental variability. Specifically, camera sensors suffer from severe low-light degradation, while LiDAR sensors encounter significant backscatter noise during heavy precipitation. These adverse conditions create a modality trust problem, as static fusion strategies fail to adaptively re-weight inputs when a specific sensor becomes unreliable.