/awesome-point-cloud-place-recognition

A list of papers about point cloud based place recognition, also known as loop closure detection in SLAM (processing)

awesome-point-cloud-place-recognition Awesome

For anyone who wants to do research about 3D point cloud based place recognition / loop closure detection. Thanks.

- Recent papers (from 2009)

Keywords

out.: outdoor   |   ind.: indoor  
pc.: point cloud   |   img.: image   |   rad.: radar  
pos.: pose  

Statistics: 🔥 code is available & stars >= 100  |  ⭐ citation >= 50

2009

  • [ICRA] Appearance-Based Loop Detection from 3D Laser Data Using the Normal Distributions Transform. [out. pc.] ⭐
  • [JFR] Automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transform. [out. pc.] ⭐

2010

  • [ICRA] Robust place recognition for 3D range data based on point features. [out. pc. pos.] ⭐

2011

  • [SSRR] Loop closure detection using small-sized signatures from 3D LIDAR data. [out. pc.]

2012

  • [UST] Real-time lidar-based place recognition using distinctive shape descriptors. [out. pc. img. pos.]
  • [TIM] 3-D-Laser-Based Scene Measurement and Place Recognition for Mobile Robots in Dynamic Indoor Environments. [ind. pc.]

2013

  • [ICRA] Place recognition using keypoint voting in large 3D lidar datasets. [out. pc.] ⭐

2015

  • [IROS] A Fast Histogram-Based Similarity Measure for Detecting Loop Closures in 3-D LIDAR Data. [code]Github stars [out. pc.]

2016

  • [IROS] M2DP: A novel 3D point cloud descriptor and its application in loop closure detection. [matlab]Github stars [python]Github stars [out. pc.] ⭐

2017

  • [ICRA] SegMatch: Segment based place recognition in 3D point clouds. [code]Github stars [out. pc. pos.] ⭐

2018

  • [IROS] Scan Context: Egocentric Spatial Descriptor for Place Recognition Within 3D Point Cloud Map. [code]Github stars [out. pc. pos.] 🔥 ⭐

  • [IROS] Stabilize an Unsupervised Feature Learning for LiDAR-based Place Recognition. [out. pc. ]

  • [IROS] Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments. [out. pc. pos.]

  • [ICRA] DELIGHT: An Efficient Descriptor for Global Localisation using LiDAR Intensities. [out. pc. ]

  • [IV] LocNet: Global Localization in 3D Point Clouds for Mobile Vehicles. [model]Github stars [code]Github stars [out. pc. pos.]

  • [RSS] SegMap: 3D Segment Mapping using Data-Driven Descriptors. [code]Github stars [out. pc.] 🔥 ⭐

  • [CVPR] PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition. [code]Github stars [out. pc.] 🔥 ⭐

  • [Sensors] Have I Seen This Place Before? A Fast and Robust Loop Detection and Correction Method for 3D Lidar SLAM. [code]Github stars [out. pc.]

  • [Sensors] Robust Place Recognition and Loop Closing in Laser-Based SLAM for UGVs in Urban Environments. [out. pc.]

2019

  • [RA-L] 1-Day Learning, 1-Year Localization: Long-Term LiDAR Localization Using Scan Context Image. [code]Github stars [out. pc. pos.] 🔥

  • [RA-L] Local Descriptor for Robust Place Recognition Using LiDAR Intensity. [out. pc.]

  • [RA-L] Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU. [out. pc. pos.]

  • [IROS] OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios. [out. pc. pos.]

  • [IROS] Semantically Assisted Loop Closure in SLAM Using NDT Histograms. [out. pc.]

  • [IROS] SeqLPD: Sequence Matching Enhanced Loop-Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles. [out. pc.]

  • [CVPR] PCAN: 3D Attention Map Learning Using Contextual Information for Point. [code]Github stars [out. pc.] ⭐

  • [ICCV] LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis. [code]Github stars [out. pc.] ⭐

  • [IJRR] SegMap: Segment-based mapping and localization using data-driven descriptors. [code]Github stars [out. pc.] 🔥

  • [TIE] Season-Invariant and Viewpoint-Tolerant LiDAR Place Recognition in GPS-Denied Environments. [out. pc.]

  • [arXiv] A fast, complete, point cloud based loop closure for LiDAR odometry and mapping. [code]Github stars [out. pc.] 🔥

2020

  • [RSS] OverlapNet - Loop Closing for 3D LiDAR-based SLAM. [code]Github stars [out. pc. pos.] 🔥

  • [ICRA] Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detection. [code]Github stars [out. pc. pos.] 🔥

  • [IROS] Semantic Graph Based Place Recognition for 3D Point Clouds. [code]Github stars [out. pc.]

  • [IROS] LiDAR Iris for Loop-Closure Detection. [code]Github stars [out. pc. pos.]

  • [IROS] Seed: A Segmentation-Based Egocentric 3D Point Cloud Descriptor for Loop Closure Detection. [out. pc.]

  • [IROS] GOSMatch: Graph-of-Semantics Matching for Detecting Loop Closures in 3D LiDAR data. [code]Github stars [out. pc.]

  • [IROS] Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments. [out. pc.]

  • [IROS] SpoxelNet: Spherical Voxel-based Deep Place Recognition for 3D Point Clouds of Crowded Indoor Spaces. [ind. pc.]

  • [IROS] Voxel-Based Representation Learning for Place Recognition Based on 3D Point Clouds. [out. pc.]

  • [IROS] SeqSphereVLAD: Sequence Matching Enhanced Orientation-invariant Place Recognition. [out. pc.]

  • [ECCV] DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization. [code]Github stars [out. pc. pos.] 🔥

  • [RAS] Global matching of point clouds for scan registration and loop detection. [out. pc.]

  • [AR] Loop detection for 3D LiDAR SLAM using segment-group matching. [out. pc.]

  • [TIE] Fast Sequence-matching Enhanced Viewpoint-invariant 3D Place Recognition. [out. pc.]

  • [Sensors] Large-Scale Place Recognition Based on Camera-LiDAR Fused Descriptor. [out. pc. img.]

  • [Sensors] A Novel Loop Closure Detection Approach Using Simplified Structure for Low-Cost LiDAR. [ind. pc.]

  • [ICARCV] Comparison of camera-based and 3D LiDAR-based place recognition across weather conditions. [out. pc. img.]

  • [ICMR] DAGC: Employing Dual Attention and Graph Convolution for Point Cloud based Place Recognition. [out. pc.]

  • [CGF] SRNet: A 3D Scene Recognition Network using Static Graph and Dense Semantic Fusion. [out. pc.]

  • [arXiv] PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition. [out. pc. img.]

2021

  • [RA-L] DiSCO: Differentiable Scan Context With Orientation. [code]Github stars [out. pc. pos.]
  • [ICRA] Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling. [code]Github stars [out. pc.]
  • [ICRA] NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation. [code]Github stars [out. pc.]
  • [ICRA] Robust Place Recognition using an Imaging Lidar. [code]Github stars [out. pc.] 🔥
  • [RA-L] LiPMatch: LiDAR Point Cloud Plane based Loop-Closure. [code]Github stars [out. pc.]
  • [RA-L] FusionVLAD: A Multi-View Deep Fusion Networks for Viewpoint-Free 3D Place Recognition. [out. pc.]
  • [RA-L] BVMatch: Lidar-Based Place Recognition Using Bird's-Eye View Images. [code]Github stars [out. pc. pos.]
  • [IROS] SSC: Semantic Scan Context for Large-Scale Place Recognition. [code]Github stars [out. pc. pos.]
  • [IROS] A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition. [code]Github stars [out. pc.]
  • [IROS] On the descriptive power of LiDAR intensity images for segment-based loop closing in 3-D SLAM. [code]Github stars [out. pc. pos.]
  • [IROS] CORAL: Colored structural representation for bi-modal place recognition. [code]Github stars [out. pc. img.]
  • [IROS] Visual Place Recognition using LiDAR Intensity Information. [out. pc.]
  • [IROS] SemSegMap - 3D Segment-Based Semantic Localization. [code]Github stars [out. img. pc. pos.] 🔥

  • [RSS] Get to the Point: Learning Lidar Place Recognition and Metric Localisation Using Overhead Imagery. [out. pc. img. pos.]

  • [CVPR] SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition. [code]Github stars [out. pc.]

  • [WACV] MinkLoc3D: Point Cloud Based Large-Scale Place Recognition. [code]Github stars [out. pc.]

  • [IJCNN] MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition. [code]Github stars [out. pc. img.]

  • [ICCCR] Weighted Scan Context: Global Descriptor with Sparse Height Feature for Loop Closure Detection. [out. pc. pos.]

  • [Frontiers] Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning. [code]Github stars [out. pc. rad.]

  • [PR] A two-level framework for place recognition with 3D LiDAR based on spatial relation graph. [out. pc.]

  • [AIM] Have I been here before? Learning to Close the Loop with LiDAR Data in Graph-Based SLAM. [code]Github stars [out. pc.]

  • [AIM] Global Place Recognition using An Improved Scan Context for LIDAR-based Localization System. [out. pc.]

  • [IJAG] FastLCD: A fast and compact loop closure detection approach using 3D point cloud for indoor mobile mapping. [ind. pc.]

  • [T-RO] Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments. [code]Github stars [out. pc. pos.] 🔥

  • [arXiv] Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognition. [code]Github stars [out. pc.]

  • [arXiv] LCDNet: Deep Loop Closure Detection for LiDAR SLAM based on Unbalanced Optimal Transport. [code]Github stars [out. pc. pos.]

  • [arXiv] SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition. [out. pc.]

  • [arXiv] AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognition. [code]Github stars [out. pc.]

  • [arXiv] TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields. [code]Github stars [out. pc.]