AI RESEARCH
Weather-Conditioned Branch Routing for Robust LiDAR-Radar 3D Object Detection
arXiv CS.CV
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ArXi:2604.05405v1 Announce Type: new Robust 3D object detection in adverse weather is highly challenging due to the varying reliability of different sensors. While existing LiDAR-4D radar fusion methods improve robustness, they predominantly rely on fixed or weakly adaptive pipelines, failing to dy-namically adjust modality preferences as environmental conditions change. To bridge this gap, we reformulate multi-modal perception as a weather-conditioned branch routing problem.