FDR-Occ Research Advances Vision-Based 3D Occupancy Prediction with Factorized Dense RoutingFDR-Occ研究进展：密集路由算法突破视觉3D占用预测瓶颈
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Researchers propose Factorized Dense Routing (FDR-Occ) for vision-based 3D occupancy prediction, addressing the Locality Bottleneck of current methods that use explicit physical projection with sparse camera rays.
FDR abstracts view transformation as unconstrained bipartite routing using hierarchical tensor contractions, achieving fully-global receptive field with sub-quadratic complexity while maintaining robustness when camera extrinsics are unreliable or absent.
The method introduces a Resolution-Context Decoupled Architecture to balance fundamental trade-offs between spatial resolution and contextual understanding in 3D space representation.