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TransLO: A Window-Based Masked Point Transformer Framework for Large-Scale LiDAR Odometry

AAAI 2023 · Point clouds › Point cloud classification · approach: LiDAR point cloud compression and completion · 37 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
use TransLO instead of LOAM with mappingLiDAR odometry · KITTI odometry 07-10 meantranslation RMSE (%): 1.278 -> 0.993Helped
use TransLO instead of LOAM with mappingLiDAR odometry · KITTI odometry 07-10 meanrotation RMSE (°/100m): 0.504 -> 0.500Helped
use TransLO instead of Nubert et al.LiDAR odometry · KITTI odometry 09/10 meantranslation RMSE (%): 1.660 -> 1.210Helped
use TransLO instead of Nubert et al.LiDAR odometry · KITTI odometry 09/10 meanrotation RMSE (°/100m): 0.685 -> 0.590Helped
use TransLO instead of LodoNetLiDAR odometry · KITTI odometry 07/08 meantranslation RMSE (%): 1.950 -> 0.965Helped
use TransLO instead of LodoNetLiDAR odometry · KITTI odometry 07/08 meanrotation RMSE (°/100m): 1.305 -> 0.420Helped
add projection-aware mask and MCFA (ablation)TransLO · KITTI odometry 07-10 meantranslation RMSE (%): 1.590 -> 0.993Helped
add projection-aware mask and MCFA (ablation)TransLO · KITTI odometry 07-10 meanrotation RMSE (°/100m): 0.848 -> 0.500Helped
add MCFA (ablation)TransLO · KITTI odometry 07-10 meantranslation RMSE (%): 1.158 -> 0.993Helped
add MCFA (ablation)TransLO · KITTI odometry 07-10 meanrotation RMSE (°/100m): 0.610 -> 0.500Helped
add WMSA (ablation)TransLO · KITTI odometry 07-10 meantranslation RMSE (%): 1.590 -> 0.993Helped
add WMSA (ablation)TransLO · KITTI odometry 07-10 meanrotation RMSE (°/100m): 0.848 -> 0.500Helped

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