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https://github.com/kxhit/awesome-point-cloud-place-recognition

A list of papers about point cloud based place recognition, also known as loop closure detection in SLAM (processing)
https://github.com/kxhit/awesome-point-cloud-place-recognition

List: awesome-point-cloud-place-recognition

lidar-point-cloud lidar-slam loop-closure-detection place-recognition point-cloud slam

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

Lists

README

        

# awesome-point-cloud-place-recognition [![Awesome](https://awesome.re/badge.svg)](https://awesome.re)

For anyone who wants to do research about 3D point cloud based place recognition / loop closure detection. [Thanks.](https://github.com/Yochengliu/awesome-point-cloud-analysis)

```diff
- Recent papers (from 2009)
```

Keywords

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

Statistics: :fire: code is available & stars >= 100  |  :star: citation >= 50

---
## 2009
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/5152712)] Appearance-Based Loop Detection from 3D Laser Data Using the Normal Distributions Transform. [__`out.`__ __`pc.`__] :star:
- [[JFR](https://doi.org/10.1002/rob.20314)] Automatic appearance-based loop detection from three-dimensional laser data using the normal distributions transform. [__`out.`__ __`pc.`__] :star:

---
## 2010
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/5509401)] Robust place recognition for 3D range data based on point features. [__`out.`__ __`pc.`__ __`pos.`__] :star:

---
## 2011
- [[SSRR](https://ieeexplore.ieee.org/document/6106765)] Loop closure detection using small-sized signatures from 3D LIDAR data. [__`out.`__ __`pc.`__]

---
## 2012
- [[UST](https://doi.org/10.1117/12.918760)] Real-time lidar-based place recognition using distinctive shape descriptors. [__`out.`__ __`pc.`__ __`img.`__ __`pos.`__]
- [[TIM](https://doi.org/10.1117/12.918760)] 3-D-Laser-Based Scene Measurement and Place Recognition for Mobile Robots in Dynamic Indoor Environments. [__`ind.`__ __`pc.`__] :star:

---
## 2013
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/6630945)] Place recognition using keypoint voting in large 3D lidar datasets. [__`out.`__ __`pc.`__] :star:

---
## 2015
- [[IROS](https://ieeexplore.ieee.org/document/7353454)] A Fast Histogram-Based Similarity Measure for Detecting Loop Closures in 3-D LIDAR Data. [[code](https://github.com/wangliuliu/histogram)]![Github stars](https://img.shields.io/github/stars/wangliuliu/histogram.svg) [__`out.`__ __`pc.`__]

---
## 2016
- [[IROS](https://ieeexplore.ieee.org/document/7759060)] M2DP: A novel 3D point cloud descriptor and its application in loop closure detection. [[matlab](https://github.com/LiHeUA/M2DP)]![Github stars](https://img.shields.io/github/stars/LiHeUA/M2DP.svg) [[python](https://github.com/adnan33/M2DP-python)]![Github stars](https://img.shields.io/github/stars/adnan33/M2DP-python.svg) [__`out.`__ __`pc.`__] :star:
---
## 2017
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/7989618)] SegMatch: Segment based place recognition in 3D point clouds. [[code](https://github.com/ZengYeGe/segmatch)]![Github stars](https://img.shields.io/github/stars/ZengYeGe/segmatch.svg) [__`out.`__ __`pc.`__ __`pos.`__] :star:
---
## 2018
- [[IROS](https://ieeexplore.ieee.org/document/8593953)] Scan Context: Egocentric Spatial Descriptor for Place Recognition Within 3D Point Cloud Map. [[code](https://github.com/irapkaist/scancontext)]![Github stars](https://img.shields.io/github/stars/irapkaist/scancontext.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire: :star:
- [[IROS](https://ieeexplore.ieee.org/document/8593562)] Stabilize an Unsupervised Feature Learning for LiDAR-based Place Recognition. [__`out.`__ __`pc.`__ ]
- [[IROS](https://ieeexplore.ieee.org/abstract/document/8594042)] Seeing the Wood for the Trees: Reliable Localization in Urban and Natural Environments. [__`out.`__ __`pc.`__ __`pos.`__]
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/8460940/)] DELIGHT: An Efficient Descriptor for Global Localisation using LiDAR Intensities. [__`out.`__ __`pc.`__ ]
- [[IV](https://ieeexplore.ieee.org/document/8500682)] LocNet: Global Localization in 3D Point Clouds for Mobile Vehicles. [[model](https://github.com/ZJUYH/LocNet_caffe)]![Github stars](https://img.shields.io/github/stars/ZJUYH/LocNet_caffe.svg) [[code](https://github.com/ZJUYH/LocNet_frontend)]![Github stars](https://img.shields.io/github/stars/ZJUYH/LocNet_frontend.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[RSS](http://www.roboticsproceedings.org/rss14/p03.pdf)] SegMap: 3D Segment Mapping using Data-Driven Descriptors. [[code](https://github.com/ethz-asl/segmap)]![Github stars](https://img.shields.io/github/stars/ethz-asl/segmap.svg) [__`out.`__ __`pc.`__] :fire: :star:
- [[RA-L](https://n.ethz.ch/~cesarc/files/RAL2018_rdube.pdf)] Incremental Segment-Based Localization in 3D Point Clouds. [[code](https://github.com/ethz-asl/segmap)]![Github stars](https://img.shields.io/github/stars/ethz-asl/segmap.svg) [__`out.`__ __`pc.`__] :fire:
- [[CVPR](https://openaccess.thecvf.com/content_cvpr_2018/papers/Uy_PointNetVLAD_Deep_Point_CVPR_2018_paper.pdf)] PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition. [[code](https://github.com/mikacuy/pointnetvlad)]![Github stars](https://img.shields.io/github/stars/mikacuy/pointnetvlad.svg) [__`out.`__ __`pc.`__] :fire: :star:
- [[Sensors](https://www.mdpi.com/1424-8220/19/1/23)] Have I Seen This Place Before? A Fast and Robust Loop Detection and Correction Method for 3D Lidar SLAM. [[code](https://github.com/michielvlaminck/m2dp-gpu)]![Github stars](https://img.shields.io/github/stars/michielvlaminck/m2dp-gpu.svg) [__`out.`__ __`pc.`__]
- [[Sensors](https://ieeexplore.ieee.org/abstract/document/8316929)] Robust Place Recognition and Loop Closing in Laser-Based SLAM for UGVs in Urban Environments. [__`out.`__ __`pc.`__]

---
## 2019
- [[RA-L](https://ieeexplore.ieee.org/document/8633942)] 1-Day Learning, 1-Year Localization: Long-Term LiDAR Localization Using Scan Context Image. [[code](https://github.com/irapkaist/scancontext)]![Github stars](https://img.shields.io/github/stars/irapkaist/scancontext.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire:
- [[RA-L](https://ieeexplore.ieee.org/document/8618373)] Local Descriptor for Robust Place Recognition Using LiDAR Intensity. [__`out.`__ __`pc.`__]
- [[RA-L](https://ieeexplore.ieee.org/document/8626476)] Learning to See the Wood for the Trees: Deep Laser Localization in Urban and Natural Environments on a CPU. [__`out.`__ __`pc.`__ __`pos.`__]
- [[IROS](https://ieeexplore.ieee.org/document/8968094/)] OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios. [__`out.`__ __`pc.`__ __`pos.`__]
- [[IROS](https://ieeexplore.ieee.org/document/8968140)] Semantically Assisted Loop Closure in SLAM Using NDT Histograms. [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/document/8967875)] SeqLPD: Sequence Matching Enhanced Loop-Closure Detection Based on Large-Scale Point Cloud Description for Self-Driving Vehicles. [__`out.`__ __`pc.`__]

- [[CVPR](https://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_PCAN_3D_Attention_Map_Learning_Using_Contextual_Information_for_Point_CVPR_2019_paper.pdf)] PCAN: 3D Attention Map Learning Using Contextual Information for Point. [[code](https://github.com/XLechter/PCAN)]![Github stars](https://img.shields.io/github/stars/XLechter/PCAN.svg) [__`out.`__ __`pc.`__] :star:
- [[ICCV](https://openaccess.thecvf.com/content_ICCV_2019/html/Liu_LPD-Net_3D_Point_Cloud_Learning_for_Large-Scale_Place_Recognition_and_ICCV_2019_paper.html)] LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis. [[code](https://github.com/Suoivy/LPD-net)]![Github stars](https://img.shields.io/github/stars/Suoivy/LPD-net.svg) [__`out.`__ __`pc.`__] :star:
- [[TIE](https://ieeexplore.ieee.org/abstract/document/8948317)] Season-Invariant and Viewpoint-Tolerant LiDAR Place Recognition in GPS-Denied Environments. [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/1909.11811)] A fast, complete, point cloud based loop closure for LiDAR odometry and mapping. [[code](https://github.com/hku-mars/loam_livox)]![Github stars](https://img.shields.io/github/stars/hku-mars/loam_livox.svg) [__`out.`__ __`pc.`__] :fire:

---
## 2020
- [[RSS](http://www.roboticsproceedings.org/rss16/p009.pdf)] OverlapNet - Loop Closing for 3D LiDAR-based SLAM. [[code](https://github.com/PRBonn/OverlapNet)]![Github stars](https://img.shields.io/github/stars/PRBonn/OverlapNet.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire: :star:
- [[ICRA](https://ieeexplore.ieee.org/document/9196764)] Intensity Scan Context: Coding Intensity and Geometry Relations for Loop Closure Detection. [[code](https://github.com/wh200720041/iscloam)]![Github stars](https://img.shields.io/github/stars/wh200720041/iscloam.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire:
- [[IROS](https://ieeexplore.ieee.org/document/9341060)] Semantic Graph Based Place Recognition for 3D Point Clouds. [[code](https://github.com/kxhit/SG_PR)]![Github stars](https://img.shields.io/github/stars/kxhit/SG_PR.svg) [__`out.`__ __`pc.`__] :fire:
- [[IROS](https://ieeexplore.ieee.org/document/9341010)] LiDAR Iris for Loop-Closure Detection. [[code](https://github.com/BigMoWangying/LiDAR-Iris)]![Github stars](https://img.shields.io/github/stars/BigMoWangying/LiDAR-Iris.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[IROS](https://ieeexplore.ieee.org/document/9341517)] Seed: A Segmentation-Based Egocentric 3D Point Cloud Descriptor for Loop Closure Detection. [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/document/9341299)] GOSMatch: Graph-of-Semantics Matching for Detecting Loop Closures in 3D LiDAR data. [[code](https://github.com/zhuyachen/GOSMatch)]![Github stars](https://img.shields.io/github/stars/zhuyachen/GOSMatch.svg) [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/document/9341667)] Gaussian Process Gradient Maps for Loop-Closure Detection in Unstructured Planetary Environments. [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/document/9341549)] SpoxelNet: Spherical Voxel-based Deep Place Recognition for 3D Point Clouds of Crowded Indoor Spaces. [__`ind.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/document/9340992)] Voxel-Based Representation Learning for Place Recognition Based on 3D Point Clouds. [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/document/9341727)] SeqSphereVLAD: Sequence Matching Enhanced Orientation-invariant Place Recognition. [__`out.`__ __`pc.`__]

- [[ECCV](https://link.springer.com/chapter/10.1007/978-3-030-58548-8_43)] DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization. [[code](https://github.com/JuanDuGit/DH3D)]![Github stars](https://img.shields.io/github/stars/JuanDuGit/DH3D.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire:

- [[RAS](https://www.sciencedirect.com/science/article/pii/S0921889019302635)] Global matching of point clouds for scan registration and loop detection. [__`out.`__ __`pc.`__]
- [[AR](https://www.tandfonline.com/doi/full/10.1080/01691864.2020.1824809?scroll=top&needAccess=true)] Loop detection for 3D LiDAR SLAM using segment-group matching. [__`out.`__ __`pc.`__]
- [[TIE](https://ieeexplore.ieee.org/document/9351776)] Fast Sequence-matching Enhanced Viewpoint-invariant 3D Place Recognition. [__`out.`__ __`pc.`__]
- [[Sensors](https://www.mdpi.com/1424-8220/20/10/2870)] Large-Scale Place Recognition Based on Camera-LiDAR Fused Descriptor. [__`out.`__ __`pc.`__ __`img.`__]
- [[Sensors](https://doi.org/10.3390/s20082299)] A Novel Loop Closure Detection Approach Using Simplified Structure for Low-Cost LiDAR. [__`ind.`__ __`pc.`__]

- [[ICARCV](https://ieeexplore.ieee.org/document/9305429)] Comparison of camera-based and 3D LiDAR-based place recognition across weather conditions. [__`out.`__ __`pc.`__ __`img.`__]
- [[ICMR](https://dl.acm.org/doi/abs/10.1145/3372278.3390693)] DAGC: Employing Dual Attention and Graph Convolution for Point Cloud based Place Recognition. [__`out.`__ __`pc.`__]
- [[CGF](https://onlinelibrary.wiley.com/doi/10.1111/cgf.14146)] SRNet: A 3D Scene Recognition Network using Static Graph and Dense Semantic Fusion. [__`out.`__ __`pc.`__]
- [[IJRR](https://journals.sagepub.com/doi/abs/10.1177/0278364919863090)] SegMap: Segment-based mapping and localization using data-driven descriptors. [[code](https://github.com/ethz-asl/segmap)]![Github stars](https://img.shields.io/github/stars/ethz-asl/segmap.svg) [__`out.`__ __`pc.`__] :fire: :star:

- [[arXiv](https://arxiv.org/abs/2008.00658)] PIC-Net: Point Cloud and Image Collaboration Network for Large-Scale Place Recognition. [__`out.`__ __`pc.`__ __`img.`__]

---
## 2021
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/9560915)] Locus: LiDAR-based Place Recognition using Spatiotemporal Higher-Order Pooling. [[code](https://github.com/csiro-robotics/locus)]![Github stars](https://img.shields.io/github/stars/csiro-robotics/locus.svg) [__`out.`__ __`pc.`__] :fire: :star:
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/9560932)] NDT-Transformer: Large-Scale 3D Point Cloud Localisation using the Normal Distribution Transform Representation. [[code](https://github.com/dachengxiaocheng/NDT-Transformer)]![Github stars](https://img.shields.io/github/stars/dachengxiaocheng/NDT-Transformer.svg) [__`out.`__ __`pc.`__]
- [[ICRA](https://ieeexplore.ieee.org/abstract/document/9562105)] Robust Place Recognition using an Imaging Lidar. [[code](https://github.com/TixiaoShan/imaging_lidar_place_recognition)]![Github stars](https://img.shields.io/github/stars/TixiaoShan/imaging_lidar_place_recognition.svg) [__`out.`__ __`pc.`__] :fire:
- [[RA-L](https://ieeexplore.ieee.org/document/9359460)] DiSCO: Differentiable Scan Context With Orientation. [[code](https://github.com/MaverickPeter/DiSCO-pytorch)]![Github stars](https://img.shields.io/github/stars/MaverickPeter/DiSCO-pytorch.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[RA-L](https://ieeexplore.ieee.org/document/9185044)] LiPMatch: LiDAR Point Cloud Plane based Loop-Closure. [[code](https://github.com/ahandsomeperson/LiPMatch)]![Github stars](https://img.shields.io/github/stars/ahandsomeperson/LiPMatch.svg) [__`out.`__ __`pc.`__]
- [[RA-L](https://ieeexplore.ieee.org/document/9361316)] FusionVLAD: A Multi-View Deep Fusion Networks for Viewpoint-Free 3D Place Recognition. [__`out.`__ __`pc.`__]
- [[RA-L](https://ieeexplore.ieee.org/abstract/document/9462410)] BVMatch: Lidar-Based Place Recognition Using Bird's-Eye View Images. [[code](https://github.com/zjuluolun/BVMatch)]![Github stars](https://img.shields.io/github/stars/zjuluolun/BVMatch.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9635904)] SSC: Semantic Scan Context for Large-Scale Place Recognition. [[code](https://github.com/lilin-hitcrt/SSC)]![Github stars](https://img.shields.io/github/stars/lilin-hitcrt/SSC.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire:
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9635878)] A Registration-aided Domain Adaptation Network for 3D Point Cloud Based Place Recognition. [[code](https://github.com/qiaozhijian/vLPD-Net)]![Github stars](https://img.shields.io/github/stars/qiaozhijian/vLPD-Net.svg) [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9636698)] On the descriptive power of LiDAR intensity images for segment-based loop closing in 3-D SLAM. [[code](https://github.com/LRMPUT/segmap_vis_views)]![Github stars](https://img.shields.io/github/stars/LRMPUT/segmap_vis_views.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9635839)] CORAL: Colored structural representation for bi-modal place recognition. [[code](https://github.com/Panyiyuan96/CORAL_Pytorch)]![Github stars](https://img.shields.io/github/stars/Panyiyuan96/CORAL_Pytorch.svg) [__`out.`__ __`pc.`__ __`img.`__]
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9636649)] Visual Place Recognition using LiDAR Intensity Information. [__`out.`__ __`pc.`__]
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9636156)] SemSegMap - 3D Segment-Based Semantic Localization. [[code](https://github.com/ethz-asl/segmap)]![Github stars](https://img.shields.io/github/stars/ethz-asl/segmap.svg) [__`out.`__ __`img.`__ __`pc.`__ __`pos.`__] :fire:
- [[IROS](https://ieeexplore.ieee.org/abstract/document/9636320)] Evaluation of Long-term LiDAR Place Recognition. [__`out.`__ __`pc.`__]
- [[RSS](http://www.roboticsproceedings.org/rss17/p003.pdf)] Get to the Point: Learning Lidar Place Recognition and Metric Localisation Using Overhead Imagery. [__`out.`__ __`pc.`__ __`img.`__ __`pos.`__]
- [[CVPR](https://openaccess.thecvf.com/content/CVPR2021/papers/Xia_SOE-Net_A_Self-Attention_and_Orientation_Encoding_Network_for_Point_Cloud_CVPR_2021_paper.pdf)] SOE-Net: A Self-Attention and Orientation Encoding Network for Point Cloud based Place Recognition. [[code](https://github.com/Yan-Xia/SOE-Net)]![Github stars](https://img.shields.io/github/stars/Yan-Xia/SOE-Net.svg) [__`out.`__ __`pc.`__]
- [[ICCV](https://openaccess.thecvf.com/content/ICCV2021/papers/Hui_Pyramid_Point_Cloud_Transformer_for_Large-Scale_Place_Recognition_ICCV_2021_paper.pdf)] Pyramid Point Cloud Transformer for Large-Scale Place Recognition. [[code](https://github.com/fpthink/PPT-Net)]![Github stars](https://img.shields.io/github/stars/fpthink/PPT-Net.svg) [__`out.`__ __`pc.`__]
- [[WACV](https://openaccess.thecvf.com/content/WACV2021/html/Komorowski_MinkLoc3D_Point_Cloud_Based_Large-Scale_Place_Recognition_WACV_2021_paper.html)] MinkLoc3D: Point Cloud Based Large-Scale Place Recognition. [[code](https://github.com/jac99/MinkLoc3D)]![Github stars](https://img.shields.io/github/stars/jac99/MinkLoc3D.svg) [__`out.`__ __`pc.`__]
- [[IJCNN](https://ieeexplore.ieee.org/abstract/document/9533373)] MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition. [[code](https://github.com/jac99/MinkLocMultimodal)]![Github stars](https://img.shields.io/github/stars/jac99/MinkLocMultimodal.svg) [__`out.`__ __`pc.`__ __`img.`__]
- [[ICCCR](https://ieeexplore.ieee.org/document/9349417)] Weighted Scan Context: Global Descriptor with Sparse Height Feature for Loop Closure Detection. [__`out.`__ __`pc.`__ __`pos.`__]
- [[Frontiers](https://www.frontiersin.org/articles/10.3389/frobt.2021.661199/full)] Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning. [[code](https://github.com/ZJUYH/radar-to-lidar-place-recognition)]![Github stars](https://img.shields.io/github/stars/ZJUYH/radar-to-lidar-place-recognition.svg) [__`out.`__ __`pc.`__ __`rad.`__]
- [[PR](https://www.sciencedirect.com/science/article/pii/S0031320321003587?casa_token=xyS6ZwbzH_cAAAAA:RdLmByqDEB193O39PJeicsKFT0XCm7APHvfVAzPzqcu9zjZ0L1tEs8YIKJIB8hnJ7p1V40O1h2pw)] A two-level framework for place recognition with 3D LiDAR based on spatial relation graph. [__`out.`__ __`pc.`__]
- [[AIM](https://ieeexplore.ieee.org/abstract/document/9517565)] Have I been here before? Learning to Close the Loop with LiDAR Data in Graph-Based SLAM. [[code](https://github.com/MarvinStuede/Sobi)]![Github stars](https://img.shields.io/github/stars/MarvinStuede/Sobi.svg) [__`out.`__ __`pc.`__]
- [[AIM](https://ieeexplore.ieee.org/abstract/document/9517663)] Global Place Recognition using An Improved Scan Context for LIDAR-based Localization System. [__`out.`__ __`pc.`__]
- [[IJAG](https://www.sciencedirect.com/science/article/pii/S0303243421001379?via%3Dihub)] FastLCD: A fast and compact loop closure detection approach using 3D point cloud for indoor mobile mapping. [__`ind.`__ __`pc.`__]
- [[T-RO](https://ieeexplore.ieee.org/abstract/document/9610172)] Scan Context++: Structural Place Recognition Robust to Rotation and Lateral Variations in Urban Environments. [[code](https://github.com/irapkaist/scancontext)]![Github stars](https://img.shields.io/github/stars/irapkaist/scancontext.svg) [__`out.`__ __`pc.`__ __`pos.`__] :fire:
- [[RCAR](https://ieeexplore.ieee.org/abstract/document/9517367)] Semantic Scan Context: Global Semantic Descriptor for LiDAR-based Place Recognition. [__`out.`__ __`pc.`__]
- [[TITS](https://ieeexplore.ieee.org/abstract/document/9523568)] PSE-Match: A Viewpoint-Free Place Recognition Method With Parallel Semantic Embedding. [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/2101.02374)] Efficient 3D Point Cloud Feature Learning for Large-Scale Place Recognition. [[code](https://github.com/fpthink/EPC-Net)]![Github stars](https://img.shields.io/github/stars/fpthink/EPC-Net.svg) [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/pdf/2103.05056.pdf)] LCDNet: Deep Loop Closure Detection for LiDAR SLAM based on Unbalanced Optimal Transport. [[code](https://github.com/robot-learning-freiburg/LCDNet)]![Github stars](https://img.shields.io/github/stars/robot-learning-freiburg/LCDNet.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[arXiv](https://arxiv.org/abs/2105.00149)] SVT-Net: Super Light-Weight Sparse Voxel Transformer for Large Scale Place Recognition. [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/2106.09637)] AttDLNet: Attention-based DL Network for 3D LiDAR Place Recognition. [[code](https://github.com/Cybonic/AttDLNet)]![Github stars](https://img.shields.io/github/stars/Cybonic/AttDLNet.svg) [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/2105.11605)] TransLoc3D : Point Cloud based Large-scale Place Recognition using Adaptive Receptive Fields. [[code](https://github.com/slothfulxtx/TransLoc3D)]![Github stars](https://img.shields.io/github/stars/slothfulxtx/TransLoc3D.svg) [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/2108.12790)] Attentive Rotation Invariant Convolution for Point Cloud-based Large Scale Place Recognition. [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/pdf/2111.00440)] Loop closure detection using local 3D deep descriptors. [__`out.`__ __`ind.`__ __`pc.`__ __`pos.`__]
- [[arXiv](https://arxiv.org/pdf/2111.13838)] DSC: Deep Scan Context Descriptor for Large-Scale Place Recognition. [__`out.`__ __`pc.`__]

---
## 2022
- [[ICRA](https://arxiv.org/abs/2204.05481)] HiTPR: Hierarchical Transformer for Place Recognition in Point Cloud. [[code](https://github.com/LouisNUST/CrackFormer-II)]![Github stars](https://img.shields.io/github/stars/LouisNUST/CrackFormer-II.svg) [__`out.`__ __`pc.`__]
- [[ICRA](https://arxiv.org/abs/2109.08336)] LoGG3D-Net: Locally Guided Global Descriptor Learning for 3D Place Recognition. [[code](https://github.com/csiro-robotics/LoGG3D-Net)]![Github stars](https://img.shields.io/github/stars/csiro-robotics/LoGG3D-Net.svg) [__`out.`__ __`pc.`__]
- [[ICRA](https://www.ipb.uni-bonn.de/wp-content/papercite-data/pdf/wiesmann2022icra.pdf)] Retriever: Point Cloud Retrieval in Compressed 3D Maps. [[code](https://github.com/PRBonn/retriever)]![Github stars](https://img.shields.io/github/stars/PRBonn/retriever.svg) [__`out.`__ __`pc.`__]
- [[ICRA](https://arxiv.org/abs/2109.08652)] AutoPlace: Robust Place Recognition with Low-cost Single-chip Automotive Radar. [[code](https://github.com/ramdrop/AutoPlace)]![Github stars](https://img.shields.io/github/stars/ramdrop/AutoPlace.svg) [__`out.`__ __`pc.`__ __`rad.`__]
- [[RA-L](https://ieeexplore.ieee.org/abstract/document/9661423)] MinkLoc3D-SI: 3D LiDAR Place Recognition With Sparse Convolutions, Spherical Coordinates, and Intensity. [[code](https://github.com/KamilZywanowski/MinkLoc3D-SI)]![Github stars](https://img.shields.io/github/stars/KamilZywanowski/MinkLoc3D-SI.svg) [__`out.`__ __`pc.`__]
- [[RA-L](https://ieeexplore.ieee.org/document/9712221)] RINet: Efficient 3D Lidar-Based Place Recognition Using Rotation Invariant Neural Network. [[code](https://github.com/lilin-hitcrt/RINet)]![Github stars](https://img.shields.io/github/stars/lilin-hitcrt/RINet.svg) [__`out.`__ __`pc.`__]
- [[RA-L](https://ieeexplore.ieee.org/document/9785497)] OverlapTransformer: An Efficient and Rotation-Invariant Transformer Network for LiDAR-Based Place Recognition. [[code](https://github.com/haomo-ai/OverlapTransformer)]![Github stars](https://img.shields.io/github/stars/haomo-ai/OverlapTransformer.svg) [__`out.`__ __`pc.`__]
- [[PRL](https://www.sciencedirect.com/science/article/abs/pii/S0167865522000782)] SC-LPR: Spatiotemporal context based LiDAR place recognition. [[code](https://github.com/Daideyun/SC-LPR)]![Github stars](https://img.shields.io/github/stars/Daideyun/SC-LPR.svg) [__`out.`__ __`pc.`__]
- [[IJPRS](https://www.sciencedirect.com/science/article/abs/pii/S0924271622001447)] A LiDAR-based single-shot global localization solution using a cross-section shape context descriptor. [[code](https://github.com/Dongxu05/CSSC)]![Github stars](https://img.shields.io/github/stars/Dongxu05/CSSC.svg) [__`out.`__ __`pc.`__]
- [[ICPR](https://arxiv.org/abs/2203.00972)] Improving Point Cloud Based Place Recognition with Ranking-based Loss and Large Batch Training
. [[code](https://github.com/jac99/MinkLoc3Dv2)]![Github stars](https://img.shields.io/github/stars/jac99/MinkLoc3Dv2.svg) [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/2203.00807)] InCloud: Incremental Learning for Point Cloud Place Recognition. [__`out.`__ __`pc.`__]
- [[arXiv](https://arxiv.org/abs/2206.03062)] Object Scan Context: Object-centric Spatial Descriptor for Place Recognition within 3D Point Cloud Map. [__`out.`__ __`pc.`__ __`pos.`__]

---
## 2023
- [[ICCV](https://openaccess.thecvf.com/content/ICCV2021/papers/Hui_Pyramid_Point_Cloud_Transformer_for_Large-Scale_Place_Recognition_ICCV_2021_paper.pdf)] CrossLoc3D: Aerial-Ground Cross-Source 3D Place Recognition. [[code](https://github.com/rayguan97/crossloc3d)]![Github stars](https://img.shields.io/github/stars/rayguan97/crossloc3d.svg) [__`out.`__ __`pc.`__ __`pos.`__]
- [[RA-L](https://ieeexplore.ieee.org/document/10065560)] Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization. [[code](https://github.com/csiro-robotics/SpectralGV)]![Github stars](https://img.shields.io/github/stars/csiro-robotics/SpectralGV.svg) [__`out.`__ __`pc.`__ __`pos.`__]