OptiMVMap selects optimal helper vehicles and applies cross-vehicle attention with noise filtering to fuse multi-vehicle views, improving vectorized map accuracy by over 10 mAP on nuScenes compared to MapTRv2.
Lio-sam: Tightly-coupled lidar inertial odometry via smoothing and mapping
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OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives
OptiMVMap selects optimal helper vehicles and applies cross-vehicle attention with noise filtering to fuse multi-vehicle views, improving vectorized map accuracy by over 10 mAP on nuScenes compared to MapTRv2.