mlsanityData to 7 Oct 2026

KISS-Matcher: Fast and Robust Point Cloud Registration Revisited

arXiv 2409.15615 ↗First posted 23 Sep 2024cs.CV cs.ROcited by 16

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Abstract (arXiv)

While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theoretic pruning, or pose solvers. In this paper, we take a holistic view on the registration problem and develop an open-source and versatile C++ library for point cloud registration, called KISS-Matcher. KISS-Matcher combines a novel feature detector, Faster-PFH, that improves over the classical fast point feature histogram (FPFH). Moreover, it adopts a k-core-based graph-theoretic pruning to reduce the time complexity of rejecting outlier correspondences. Finally, it combines these modules in a complete, user-friendly, and ready-to-use pipeline. As verified by extensive experiments, KISS-Matcher has superior scalability and broad applicability, achieving a substantial speed-up compared to state-of-the-art outlier-robust registration pipelines while preserving accuracy. Our code will be available at https://github.com/MIT-SPARK/KISS-Matcher.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 33 of its 76 references that are in the map. First posted on arXiv 23 Sep 2024.

Builds on

33 of 76 references.

References · 33

  1. 2018Open3D: A Modern Library for 3D Data Processingcited by 717
  2. 2019Deep Closest Point: Learning Representations for Point Cloud Registrationcited by 318
  3. 2020PREDATOR: Registration of 3D Point Clouds with Low Overlapcited by 287
  4. 2020TEASER: Fast and Certifiable Point Cloud Registrationcited by 274
  5. 2020Deep Global Registrationcited by 228
  6. 2020D3Feat: Joint Learning of Dense Detection and Description of 3D Local Featurescited by 175
  7. 2021FAST-LIO2: Fast Direct LiDAR-inertial Odometrycited by 170
  8. 2016Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registrationcited by 159
  9. 2020SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registrationcited by 141
  10. 2022KISS-ICP: In Defense of Point-to-Point ICP -- Simple, Accurate, and Robust Registration If Done the Right Waycited by 132
  11. 20183DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registrationcited by 100
  12. 2019Graduated Non-Convexity for Robust Spatial Perception: From Non-Minimal Solvers to Global Outlier Rejectioncited by 92
21 more
  1. 2020Learning multiview 3D point cloud registrationcited by 78
  2. 2021LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMcited by 67
  3. 2021Learning general and distinctive 3D local deep descriptors for point cloud registrationcited by 41
  4. 2023A Survey on Global LiDAR Localization: Challenges, Advances and Open Problemscited by 40
  5. 2020ROBIN: a Graph-Theoretic Approach to Reject Outliers in Robust Estimation using Invariantscited by 38
  6. 2021Patchwork: Concentric Zone-based Region-wise Ground Segmentation with Ground Likelihood Estimation Using a 3D LiDAR Sensorcited by 28
  7. 2021Range Image-based LiDAR Localization for Autonomous Vehiclescited by 25
  8. 2022STD: Stable Triangle Descriptor for 3D place recognitioncited by 23
  9. 2020Distinctive 3D local deep descriptorscited by 21
  10. 2022A Single Correspondence Is Enough: Robust Global Registration to Avoid Degeneracy in Urban Environmentscited by 19
  11. 2023Quatro++: Robust Global Registration Exploiting Ground Segmentation for Loop Closing in LiDAR SLAMcited by 18
  12. 2021RANSIC: Fast and Highly Robust Estimation for Rotation Search and Point Cloud Registration using Invariant Compatibilitycited by 16
  13. 2023Resilient and Distributed Multi-Robot Visual SLAM: Datasets, Experiments, and Lessons Learnedcited by 16
  14. 2013Parallel Maximum Clique Algorithms with Applications to Network Analysis and Storagecited by 15
  15. 2021PHASER: a Robust and Correspondence-free Global Pointcloud Registrationcited by 15
  16. 2021TriVoC: Efficient Voting-based Consensus Maximization for Robust Point Cloud Registration with Extreme Outlier Ratioscited by 11
  17. 2023Segregator: Global Point Cloud Registration with Semantic and Geometric Cuescited by 11
  18. 2019Outlier-Robust Spatial Perception: Hardness, General-Purpose Algorithms, and Guaranteescited by 10
  19. 2021Robust Place Recognition using an Imaging Lidarcited by 9
  20. 20233D-BBS: Global Localization for 3D Point Cloud Scan Matching Using Branch-and-Bound Algorithmcited by 8
  21. 2022Learning to Register Unbalanced Point Pairscited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 6; 2026: 10.

16 papers.

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  1. 2025Articulated Object Estimation in the Wildcited by 18
  2. 2025Register Any Point: Scaling 3D Point Cloud Registration by Flow Matchingcited by 8
  3. 2026Picasso: Holistic Scene Reconstruction with Physics-Constrained Samplingcited by 4
  4. 2025A Review on Geometry and Surface Inspection in 3D Concrete Printingcited by 2
  5. 2025Fast globally optimal Truncated Least Squares point cloud registration with fixed rotation axiscited by 2
  6. 2026Leveraging Previous-Traversal Point Cloud Map Priors for Camera-Based 3D Object Detection and Trackingcited by 2
  7. 2025Have We Scene It All? Scene Graph-Aware Deep Point Cloud Compressioncited by 1
  8. 2026Towards Zero-Shot Point Cloud Registration Across Diverse Scales, Scenes, and Sensor Setupscited by 1
  9. 2026BEV-SLD: Self-Supervised Scene Landmark Detection for Global Localization with LiDAR Bird's-Eye View Imagescited by 1
  10. 2025Registration of 3D Point Sets Using Exponential-based Similarity Matrixcited by 0
  11. 2026Paparazzo: Active Mapping of Moving 3D Objectscited by 0
  12. 2026Aerial-ground LiDAR place recognition with patch-level self-supervised learning and expanded reciprocal re-rankingcited by 0
4 more
  1. 2026InLiER: Learning-Free Heterogeneous LiDAR Place Recognition via Intermediate Mixed-Radix Structural Keypoint Tokenizationcited by 0
  2. 2026Accelerating Large-scale Bundle Adjustment for LiDAR Mapping via Parallel Computingcited by 0
  3. 2026CVSD-Reg: Cross-Modal Visual Semantic Prior Distillation for Robust LiDAR Registrationcited by 0
  4. 2026PARTE: Plane-Assisted Robust Transformation Estimation for Point Cloud Registrationcited by 0