Point Cloud Registration
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Benchmarks
ETH (trained on 3DMatch)
3DMatch Benchmark
KITTI (trained on 3DMatch)
3DLoMatch (10-30% overlap)
KITTI (FCGF setting)
FPv1
KITTI
FP-O-E
FP-O-H
FP-O-M
FP-R-E
FP-R-H
FP-R-M
FP-T-E
FP-T-H
FP-T-M
3DMatch (trained on KITTI)
KITTI (Distant PCR)
nuScenes (Distant PCR)
3RScan
Most implemented
Open3D: A Modern Library for 3D Data Processing
SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization
TEASER: Fast and Certifiable Point Cloud Registration
PointNetLK: Robust & Efficient Point Cloud Registration using PointNet
PREDATOR: Registration of 3D Point Clouds with Low Overlap
RPM-Net: Robust Point Matching using Learned Features
Papers
CVSD-Reg: Cross-Modal Visual Semantic Prior Distillation for Robust LiDAR Registration
Learning-based global point cloud registration has achieved remarkable progress, yet its reliance on geometric representations makes existing methods sensitive to variations in point density, scan pattern, viewpoint, and…
Point Cloud RegistrationSHReg: Strictly Rotation-Equivariant Point Cloud Registration via Spherical Harmonics
Point cloud registration critically depends on local features that are both distinctive and robust to arbitrary 3D rotations. Existing learning-based methods typically approximate rotation invariance via fragile local re…
Point Cloud RegistrationData AugmentationDINE: Distance Is Not Enough -- Learning Global Deformation Priors for Robust Soft-Tissue Point Cloud Registration
Non-rigid point cloud registration is central to soft-tissue shape analysis, but large deformations, noise, and outliers make correspondence estimation challenging. Most learning-based methods rely on local objectives su…
Point Cloud RegistrationImage-to-Point Cloud Registration Made Easy with Rectified Flow-based LiDAR Upsampling
Image-to-Point Cloud Registration (I2P) is essential for integrating camera and LiDAR in perception and autonomous systems, yet the modality gap between images and point clouds makes it difficult to achieve both high acc…
Point Cloud RegistrationPoint CloudsNeural LiDAR Bundle Adjustment
Recent research has achieved remarkable novel view rendering and scene reconstruction results with Neural Radiance Field (NeRF), including extensions to the LiDAR modality. Few studies have, however, explored the key des…
Point Cloud RegistrationSinkhorn-CPD: Robust point cloud registration via unbalanced entropic optimal transport
Coherent Point Drift (CPD) is widely used for rigid point cloud registration because of its soft correspondences and closed-form parameter updates. However, CPD's target-side marginal constraint forces every observation,…
Point Cloud Registration