Combining data augmentation, cross-modal attention fusion, and modality dropout training improves robustness of camera-LiDAR HD map construction under 13 synthetic sensor corruptions and raises clean nuScenes mAP to 77.0.
Diffmap: Enhancing map segmentation with map prior using diffusion model,
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What Really Matters for Robust Multi-Sensor HD Map Construction?
Combining data augmentation, cross-modal attention fusion, and modality dropout training improves robustness of camera-LiDAR HD map construction under 13 synthetic sensor corruptions and raises clean nuScenes mAP to 77.0.