NTR adds a self-distillation masked latent reconstruction objective that uses only scene tokens to reconstruct masked patch features, improving visual representation quality and planning performance in end-to-end autonomous driving.
Coto-Elena, J.E
2 Pith papers cite this work. Polarity classification is still indexing.
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BIEVR-LIO improves robustness of LiDAR-inertial odometry by representing maps as voxel-wise oriented height images and sampling points only from geometrically informative regions.
citing papers explorer
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NTR: Neural Token Reconstruction for Scene Token Bottleneck in End-to-End Driving
NTR adds a self-distillation masked latent reconstruction objective that uses only scene tokens to reconstruct masked patch features, improving visual representation quality and planning performance in end-to-end autonomous driving.
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BIEVR-LIO: Robust LiDAR-Inertial Odometry through Bump-Image-Enhanced Voxel Maps
BIEVR-LIO improves robustness of LiDAR-inertial odometry by representing maps as voxel-wise oriented height images and sampling points only from geometrically informative regions.