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.
Mapdistill: Boosting efficient camera-based hd map construction via camera-lidar fusion model distillation,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.CV 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
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.