mlsanityData to 7 Oct 2026

SegMatch: Segment based loop-closure for 3D point clouds

arXiv 1609.07720 ↗First posted 25 Sep 2016cs.ROcited by 48

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Abstract (arXiv)

Loop-closure detection on 3D data is a challenging task that has been commonly approached by adapting image-based solutions. Methods based on local features suffer from ambiguity and from robustness to environment changes while methods based on global features are viewpoint dependent. We propose SegMatch, a reliable loop-closure detection algorithm based on the matching of 3D segments. Segments provide a good compromise between local and global descriptions, incorporating their strengths while reducing their individual drawbacks. SegMatch does not rely on assumptions of "perfect segmentation", or on the existence of "objects" in the environment, which allows for reliable execution on large scale, unstructured environments. We quantitatively demonstrate that SegMatch can achieve accurate localization at a frequency of 1Hz on the largest sequence of the KITTI odometry dataset. We furthermore show how this algorithm can reliably detect and close loops in real-time, during online operation. In addition, the source code for the SegMatch algorithm will be made available after publication.

Key facts. Cited by 48 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Sep 2016.

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Citing papers per year: 2021: 13; 2022: 8; 2023: 12; 2024: 4; 2025: 5; 2026: 6.

48 papers.

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  1. 2021LCDNet: Deep Loop Closure Detection and Point Cloud Registration for LiDAR SLAMcited by 67
  2. 2021MinkLoc++: Lidar and Monocular Image Fusion for Place Recognitioncited by 41
  3. 2021NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representationcited by 38
  4. 2021SSC: Semantic Scan Context for Large-Scale Place Recognitioncited by 24
  5. 2022STD: Stable Triangle Descriptor for 3D place recognitioncited by 23
  6. 2021Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognitioncited by 21
  7. 2021SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closurecited by 14
  8. 2022MultiRes-NetVLAD: Augmenting Place Recognition Training with Low-Resolution Imagerycited by 14
  9. 2021Graph-based Thermal-Inertial SLAM with Probabilistic Neural Networkscited by 12
  10. 2023G3Reg: Pyramid Graph-based Global Registration using Gaussian Ellipsoid Modelcited by 11
  11. 2022HiTPR: Hierarchical Transformer for Place Recognition in Point Cloudcited by 10
  12. 2022BoxGraph: Semantic Place Recognition and Pose Estimation from 3D LiDARcited by 10
36 more
  1. 2021DARE-SLAM: Degeneracy-Aware and Resilient Loop Closing in Perceptually-Degraded Environmentscited by 9
  2. 2023Applications of Spiking Neural Networks in Visual Place Recognitioncited by 9
  3. 2021Loop closure detection using local 3D deep descriptorscited by 8
  4. 2022Robust Double-Encoder Network for RGB-D Panoptic Segmentationcited by 8
  5. 2023Contour Context: Abstract Structural Distribution for 3D LiDAR Loop Detection and Metric Pose Estimationcited by 8
  6. 2021Zero-Shot Reinforcement Learning on Graphs for Autonomous Exploration Under Uncertaintycited by 6
  7. 2024RecNet: An Invertible Point Cloud Encoding through Range Image Embeddings for Multi-Robot Map Sharing and Reconstructioncited by 6
  8. 2025ForestLPR: LiDAR Place Recognition in Forests Attentioning Multiple BEV Density Imagescited by 6
  9. 2023SEM-GAT: Explainable Semantic Pose Estimation using Learned Graph Attentioncited by 5
  10. 2024ModaLink: Unifying Modalities for Efficient Image-to-PointCloud Place Recognitioncited by 5
  11. 2022GraffMatch: Global Matching of 3D Lines and Planes for Wide Baseline LiDAR Registrationcited by 3
  12. 2023A Unified BEV Model for Joint Learning of 3D Local Features and Overlap Estimationcited by 3
  13. 2024That's My Point: Compact Object-centric LiDAR Pose Estimation for Large-scale Outdoor Localisationcited by 3
  14. 2023Real-Time Simultaneous Localization and Mapping with LiDAR intensitycited by 2
  15. 2023Pose-Graph Attentional Graph Neural Network for Lidar Place Recognitioncited by 2
  16. 2023DeepPointMap: Advancing LiDAR SLAM with Unified Neural Descriptorscited by 2
  17. 2025LiDAR Loop Closure Detection using Semantic Graphs with Graph Attention Networkscited by 2
  18. 2021On the descriptive power of LiDAR intensity images for segment-based loop closing in 3-D SLAMcited by 1
  19. 2021DSC: Deep Scan Context Descriptor for Large-Scale Place Recognitioncited by 1
  20. 2022Descriptellation: Deep Learned Constellation Descriptorscited by 1
  21. 2022A Survey on Visual Map Localization Using LiDARs and Camerascited by 1
  22. 2023BPT: Binary Point Cloud Transformer for Place Recognitioncited by 1
  23. 2023Converting Depth Images and Point Clouds for Feature-based Pose Estimationcited by 1
  24. 2023FAKEPCD: Fake Point Cloud Detection via Source Attributioncited by 1
  25. 2024QuadricsReg: Large-Scale Point Cloud Registration using Quadric Primitivescited by 1
  26. 2026BEVMAPMATCH: Multimodal BEV Neural Map Matching for Robust Re-Localization of Autonomous Vehiclescited by 1
  27. 2021Deep Weakly Supervised Positioningcited by 0
  28. 2023Scene 3-D Reconstruction System in Scattering Mediumcited by 0
  29. 2025PNE-SGAN: Probabilistic NDT-Enhanced Semantic Graph Attention Network for LiDAR Loop Closure Detectioncited by 0
  30. 2025Gaussian Semantic Field for One-shot LiDAR Global Localizationcited by 0
  31. 2025Query-Calibrated Segmental Admission for Descriptor-Agnostic LiDAR Loop Closure in Repetitive Environmentscited by 0
  32. 2026WHU-PCPR: A cross-platform heterogeneous point cloud dataset for place recognition in complex urban scenescited by 0
  33. 2026How to rewrite the stars: Mapping your orchard over time through constellations of fruitscited by 0
  34. 2026Loop Closure via Maximal Cliques in 3D LiDAR-Based SLAMcited by 0
  35. 2026Self-Healing Visual Recovery for Autonomous Ground Vehicles Using Camera-Only Visual Odometrycited by 0
  36. 2026PARTE: Plane-Assisted Robust Transformation Estimation for Point Cloud Registrationcited by 0