Point Cloud Registration
185 papers with code • 22 benchmarks • 10 datasets
Point Cloud Registration is a fundamental problem in 3D computer vision and photogrammetry. Given several sets of points in different coordinate systems, the aim of registration is to find the transformation that best aligns all of them into a common coordinate system. Point Cloud Registration plays a significant role in many vision applications such as 3D model reconstruction, cultural heritage management, landslide monitoring and solar energy analysis.
Benchmarks
These leaderboards are used to track progress in Point Cloud Registration
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Libraries
Use these libraries to find Point Cloud Registration models and implementationsDatasets
KITTI
3DMatch
DeformingThings4D
3RScan
UrbanLoco
4DMatch
3DCSR dataset
FPv1
FAUST-partial
CODD
Latest papers
Efficient and Robust Point Cloud Registration via Heuristics-guided Parameter Search
Our strategy largely reduces the search space and can guarantee accuracy with only a few inlier samples, therefore enjoying an excellent trade-off between efficiency and robustness.
SG-PGM: Partial Graph Matching Network with Semantic Geometric Fusion for 3D Scene Graph Alignment and Its Downstream Tasks
dfki-av/sg-pgm
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The alignment between 3D scene graphs is the first step of many downstream tasks such as scene graph aided point cloud registration, mosaicking, overlap checking, and robot navigation.
Addressing the generalization of 3D registration methods with a featureless baseline and an unbiased benchmark
DavidBoja/exhaustive-grid-search
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Machine Vision and Applications 2024
The FP benchmark addresses the limitations of the current benchmarks: lack of data and parameter range variability, and allows to evaluate the strengths and weaknesses of a 3D registration method w. r. t.
VRHCF: Cross-Source Point Cloud Registration via Voxel Representation and Hierarchical Correspondence Filtering
guiyuzhao/vrhcf
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Our method exhibits versatile applicability and excels in both traditional homologous registration and challenging cross-source registration scenarios.
FastMAC: Stochastic Spectral Sampling of Correspondence Graph
As such, the core of our method is the stochastic spectral sampling of correspondence graph.
Extend Your Own Correspondences: Unsupervised Distant Point Cloud Registration by Progressive Distance Extension
liuquan98/eyoc
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Registration of point clouds collected from a pair of distant vehicles provides a comprehensive and accurate 3D view of the driving scenario, which is vital for driving safety related applications, yet existing literature suffers from the expensive pose label acquisition and the deficiency to generalize to new data distributions.
PCR-99: A Practical Method for Point Cloud Registration with 99% Outliers
We propose a robust method for point cloud registration that can handle both unknown scales and extreme outlier ratios.
CLIPPER+: A Fast Maximal Clique Algorithm for Robust Global Registration
The registration problem can be formulated as a graph and solved by finding its maximum clique.
Registration of algebraic varieties using Riemannian optimization
Our approach is particularly useful when the two point clouds describe different parts of an objects (which may not even be overlapping), on the condition that the surface of the object may be well approximated by a set of polynomial equations.
Iterative Feedback Network for Unsupervised Point Cloud Registration
ivanxie416/ifnet
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In this paper, we propose a novel Iterative Feedback Network (IFNet) for unsupervised point cloud registration, in which the representation of low-level features is efficiently enriched by rerouting subsequent high-level features.
