Reproduce “ReinSeg: Retrieval-Guided Bounded Multimodal Refinement for 3-D Road Anomaly Segmentation” on OpenResearch
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About this paper
Haifa Zhang, Yijing Wang, Zhiqiang Zuo
ReinSeg uses camera context to improve point-level LiDAR anomaly ranking while preserving each point’s measured location. Occupied LiDAR regions retrieve relevant context from eight camera views, and a relative-norm bound limits changes to LiDAR features before the frozen LIDO scorer ranks points. On STU validation, AP rises from 27.54% to 35.67%, while FPR95 falls from 34.85% to 10.61%, establishing results only on this held-out set.
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