A list of references on lidar point cloud processing for autonomous driving
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Lidar Point clound processing for Autonomous Driving

A list of references on lidar point cloud processing for autonomous driving

LiDAR Pointcloud Clustering/Semantic Segmentation/Plane extraction

Tasks : Road/Ground extraction, plane extraction, Semantic segmentation, open set instance segmentation, Clustering

  • Fast Segmentation of 3D Point Clouds: A Paradigm on LiDAR Data for Autonomous Vehicle Applications ICRA 2017 [git, pdf]
  • Time-series LIDAR Data Superimposition for Autonomous Driving [pdf]
  • Fast segmentation of 3D point clouds for ground vehicles [ieee]
  • An Improved RANSAC for 3D Point Cloud Plane Segmentation Based on Normal Distribution Transformation Cells
  • Segmentation of Dynamic Objects from Laser Data [pdf]
  • A Fast Ground Segmentation Method for 3D Point Cloud [pdf]
  • Ground Estimation and Point Cloud Segmentation using SpatioTemporal Conditional Random Field [pdf]
  • Real-Time Road Segmentation Using LiDAR Data Processing on an FPGA [pdf]
  • Efficient Online Segmentation for Sparse 3D Laser Scans [pdf], [git]
  • CNN for Very Fast Ground Segmentation in Velodyne LiDAR Data [pdf]
  • A Comparative Study of Segmentation and Classification Methods for 3D Point Clouds 2016 Masters Thesis [pdf]
  • Fast Multi-pass 3D Point Segmentation Based on a Structured Mesh Graph for Ground Vehicles pdf video
  • RangeNet++: Fast and Accurate LiDAR Semantic Segmentation [[link](], [pdf]
  • Circular Convolutional Neural Networks for Panoramic Images and Laser Data pdf
  • Efficient Convolutions for Real-Time Semantic Segmentation of 3D Point Clouds [pdf]
  • Identifying Unknown Instances for Autonomous Driving/Open-set instance segmentation algorithm CoRL 2019 [pdf]
  • RIU-Net: Embarrassingly simple semantic segmentation of3D LiDAR point cloud. [pdf, LU-net]
  • SalsaNet: Fast Road and Vehicle Segmentation in LiDAR Point Clouds for Autonomous Driving [pdf]
  • SqueezeSegV3: Spatially-Adaptive Convolution for Efficient Point-Cloud Segmentation [link]
  • PolarNet: An Improved Grid Representation for Online LiDAR Point Clouds Semantic Segmentation [link]
  • Scan-based Semantic Segmentation of LiDAR Point Clouds: An Experimental Study IV 2020 [pdf]
  • Plane Segmentation Based on the Optimal-vector-field in LiDAR Point Clouds [link]
  • Semantic Segmentation of 3D LiDAR Data in Dynamic Scene Using Semi-supervised Learning [link]
  • Learning Hierarchical Semantic Segmentations of LIDAR Data 3DV 2015 [pdf]
  • EfficientLPS: Efficient LiDAR Panoptic Segmentation 2021 pdf, video
  • 4D Panoptic LiDAR Segmentation 2021 [pdf]
  • urban_road_filter: a real-time LIDAR-based urban road and sidewalk detection algorithm for autonomous vehicles [git, video, pdf, code]

Pointcloud Density & Compression

  • DBSCAN : A density-based algorithm for discovering clusters in large spatial databases with noise (1996) [pdf]
  • Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection pdf
  • Building Maps for Autonomous Navigation Using Sparse Visual SLAM Features [pdf]
  • STD: Sparse-to-Dense 3D Object Detector for Point Cloud pdf
  • Fast semantic segmentation of 3d point clounds with strongly varying density [pdf]
  • The Perfect Match: 3D Point Cloud Matching with Smoothed Densities [pdf, code]
  • Deep Compression for Dense Point Cloud Maps [link]
  • Improved Deep Point Cloud Geometry Compression [pdf, git]
  • Real-Time Spatio-Temporal LiDAR Point Cloud Compression [pdf]

Registration and Localization

  • A Review of Point Cloud Registration Algorithms for Mobile Robotics 2015 [pdf]
  • LOAM: Lidar Odometry and Mapping in Real-time RSS 2014 [pdf, video]
  • Fast Planar Surface 3D SLAM Using LIDAR 2016 [pdf]
  • Point Clouds Registration with Probabilistic Data Association IROS 2016 [git]
  • Robust LIDAR Localization using Multiresolution Gaussian Mixture Maps for Autonomous Driving IJRR 2017 [pdf], [Thesis]
  • Automatic Merging of Lidar Point-Clouds Using Data from Low-Cost GPS/IMU Systems SPIE 2011 [pdf]
  • Fast and Robust 3D Feature Extraction from Sparse Point Clouds [pdf]
  • 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration [pdf]
  • Incremental Segment-Based Localization in 3D Point Clouds [pdf]
  • OverlapNet: Loop Closing for LiDAR-based SLAM, RSS 2020 [[pdf](OverlapNet: Loop Closing for LiDAR-based SLAM), git, video]
  • CorsNet: 3D Point Cloud Registration by Deep Neural Network, ICRA 2020 [link]
  • LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis ICCV 2019 [pdf]
  • DH3D: Deep Hierarchical 3D Descriptors for Robust Large-Scale 6DoF Relocalization [pdf,project, video]
  • Localisation using LiDAR and Camera Localisation in low visibility road conditions Master’s thesis 2017 [pdf]
  • Monocular Camera Localization in 3D LiDAR Maps IROS 2016 [pdf]

Feature Extraction

  • Fast Feature Detection and Stochastic Parameter Estimation of Road Shape using Multiple LIDAR [pdf]
  • Finding Planes in LiDAR Point Clouds for Real-Time Registration [pdf]
  • Online detection of planes in 2D lidar [pdf]
  • A Fast RANSAC–Based Registration Algorithm for Accurate Localization in Unknown Environments using LIDAR Measurements [pdf]
  • Hierarchical Plane Extraction (HPE): An Efficient Method For Extraction Of Planes From Large Pointcloud Datasets [pdf]
  • A Fast and Accurate Plane Detection Algorithm for Large Noisy Point Clouds Using Filtered Normals and Voxel Growing [pdf]
  • SPLATNet: Sparse Lattice Networks for Point Cloud Processing CVPR 2018 [pdf, code]
  • PointContrast: Unsupervised Pre-training for 3D Point Cloud Understanding, 4D-VISION workshop at ECCV'2020 [pdf, workshop]

Object detection and Tracking

  • Learning a Real-Time 3D Point Cloud Obstacle Discriminator via Bootstrapping pdf
  • Terrain-Adaptive Obstacle Detection [pdf]
  • 3D Object Detection from Roadside Data Using Laser Scanners [pdf]
  • 3D Multiobject Tracking for Autonomous Driving : Masters thesis A S Abdul Rahman
  • Motion-based Detection and Tracking in 3D LiDAR Scans [pdf]
  • Lidar-histogram for fast road and obstacle detection [pdf]
  • End-to-end Learning of Multi-sensor 3D Tracking by Detection pdf
  • Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection pdf
  • Deep tracking in the wild: End-to-end tracking using recurrent neural networks [pdf]
  • Leveraging Heteroscedastic Aleatoric Uncertainties for Robust Real-Time LiDAR 3D Object Detection [pdf], video]
  • VoxelNet: End-to-End Learning for Point Cloud Based 3D Object Detection CVPR 2018 [pdf, code]
  • PIXOR: Real-time 3D Object Detection from Point Clouds CVPR 2018 [pdf]
  • Deep Multi-modal Object Detection and Semantic Segmentation for Autonomous Driving: Datasets, Methods, and Challenges [pdf]
  • Low resolution lidar-based multi-object tracking for driving applications [pdf]
  • Patch Refinement -- Localized 3D Object Detection [pdf]
  • PointPillars: Fast Encoders for Object Detection from Point Clouds CVPR 2019 [pdf]
  • StarNet: Targeted Computation for Object Detection in Point Clouds NeurIPS 2019 ML4AD [pdf]
  • PV-RCNN: Point-Voxel Feature Set Abstraction for 3D Object Detection CVPR 2020 [pdf]
  • LaserNet: An Efficient Probabilistic 3D Object Detector for Autonomous Driving CVPR 2019 [pdf]
  • Range Conditioned Dilated Convolutions for Scale Invariant 3D Object Detection 2020 [pdf]
  • AFDet: Anchor Free One Stage 3D Object Detection [pdf]
  • SA-SSD: Structure Aware Single-stage 3D Object Detection from Point Cloud (CVPR 2020) [pdf, git]
  • Any Motion Detector: Learning Class-agnostic Scene Dynamics from a Sequence of LiDAR Point Clouds, ICRA 2020 [pdf]
  • MVLidarNet: Real-Time Multi-Class Scene Understanding for Autonomous Driving Using Multiple Views [link, video]
  • Learning to Optimally Segment Point Clouds, ICRA 2020 [pdf, video, git]
  • What You See is What You Get: Exploiting Visibility for 3D Object Detection [pdf, video, project]

Classification/Supervised Learning

  • PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation [link, link2]
  • SqueezeSeg: Convolutional Neural Nets with Recurrent CRF for Real-Time Road-Object Segmentation from 3D LiDAR Point Cloud pdf
  • Improving LiDAR Point Cloud Classification using Intensities and Multiple Echoes [pdf]
  • DepthCN: Vehicle Detection Using 3D-LIDAR and ConvNet [pdf]
  • 3D Object Localisation with Convolutional Neural Networks [Thesis]
  • SqueezeSegV2: Improved Model Structure and Unsupervised Domain Adaptation for Road-Object Segmentation from a LiDAR Point Cloud [pdf]
  • PointSeg: Real-Time Semantic Segmentation Based on 3D LiDAR Point Cloud [pdf]
  • Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks [pdf]
  • ChipNet: Real-Time LiDAR Processing for Drivable Region Segmentation on an FPGA [pdf]

Maps / Grids / HD Maps / Occupancy grids/ Prior Maps

  • Hierarchies of Octrees for Efficient 3D Mapping pdf
  • Adaptive Resolution Grid Mapping using Nd-Tree [ieee], [pdf, video]
  • LIDAR-Data Accumulation Strategy To Generate High Definition Maps For Autonomous Vehicles [link]
  • Long-term robot mapping in dynamic environments, Aisha Naima Walcott Thesis MIT 2011 [link]
  • Long-term 3D map maintenance in dynamic environments ICRA 2014 [pdf, video]
  • Detection and Tracking of Moving Objects Using 2.5D Motion Grids ITSC 2015 [pdf]
  • Autonomous Vehicle Navigation in Rural Environments without Detailed Prior Maps ICRA 2018 [pdf, video]
  • 3D Lidar-based Static and Moving Obstacle Detection in Driving Environments: an approach based on voxels and multi-region ground planes [pdf]
  • Spatio–Temporal Hilbert Maps for Continuous Occupancy Representation in Dynamic Environments [pdf]
  • Dynamic Occupancy Grid Prediction for Urban Autonomous Driving: A Deep Learning Approach with Fully Automatic Labeling [pdf]
  • Mobile Laser Scanned Point-Clouds for Road Object Detection and Extraction: A Review [pdf]
  • Efficient Continuous-time SLAM for 3D Lidar-based Online Mapping [pdf]
  • DeLS-3D: Deep Localization and Segmentation with a 3D Semantic Map [pdf],video]
  • Recurrent-OctoMap: Learning State-based Map Refinement for Long-Term Semantic Mapping with 3D-Lidar Data [pdf]
  • HDNET: Exploiting HD Maps for 3D Object Detection [pdf]
  • Mapping with Dynamic-Object Probabilities Calculated from Single 3D Range Scans ICRA 2018 [pdf]

End-To-End Learning

  • Monocular Fisheye Camera Depth Estimation Using Semi-supervised Sparse Velodyne Data [pdf]
  • Fast and Furious: Real Time End-to-End 3D Detection, Tracking and Motion Forecasting with a Single Convolutional Net [pdf]

Simulated pointclouds / Simulators

  • Virtual Generation of Lidar Data for Autonomous Vehicles Simulation of a lidar sensor inside a virtual world Bachelors Thesis 2017 pdf
  • A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving ACM 2018 [pdf]
  • Udacity based simulator [link, git]
  • Tutorial on Gazebo to simulate raycasting from Velodyne lidar [link]
  • Udacity Driving Dataset [link]
  • Virtual KITTI [link]
  • SynthCity: A large-scale synthetic point cloud 2019 [dataset, pdf]
  • Precise Synthetic Image and LiDAR (PreSIL) Dataset for Autonomous Vehicle Perception [link]
  • Fast Synthetic LiDAR Rendering via Spherical UV Unwrapping of Equirectangular Z-Buffer Images 2020 [pdf]

Lidar Datasets

  • nuScenes : public large-scale dataset for autonomous driving [dataset]
    • nuScenes-lidarseg will be released in Q2 2020. [link]
  • Ford Campus Vision and Lidar Data Set [pdf, dataset]
  • Oxford RobotCar dataset dataset 1 Year, 1000km: The Oxford RobotCar Dataset pdf
  • LiDAR-Video Driving Dataset: Learning Driving Policies Effectively [pdf]
  • KAIST Complex Urban Data Set Dataset [dataset]
  • Semantic 3D 2017 dataset
  • Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification [pdf dataset]
  • Semantic KITTI 2019 [dataset]
  • A*3D: An Autonomous Driving Dataset in Challeging Environments [dataset], video]
  • HD Map Dataset & Localization Dataset NAVER Labs : [link]
  • Argoverse by ARGO AI : Two public datasets supported by highly detailed maps to test, experiment, and teach self-driving vehicles how to understand the world around them. [link]
  • Lyft dataset [link]
  • SemanticPOSS: A Point Cloud Dataset with Large Quantity of Dynamic Instances [link, pdf]
  • A2D2 Audi dataset [link]
  • PandaSet : Public large-scale dataset for autonomous driving provided by Hesai & Scale. [link]
  • Toronto-3D: A Large-scale Mobile LiDAR Dataset for Semantic Segmentation of Urban Roadways [pdf, dataset]

Spatio-Temporal, Movement, Flow estimation in Pointclouds

  • Rigid Scene Flow for 3D LiDAR Scans IROS 2016 [pdf]
  • Deep Lidar CNN to Understand the Dynamics of Moving Vehicles [pdf]
  • Learning motion field of LiDAR point cloud with convolutional networks [link]
  • Hallucinating Dense Optical Flow from Sparse Lidar for Autonomous Vehicles [pdf video]
  • FlowNet3D: Learning Scene Flow in 3D Point Clouds CVPR 2019 [pdf, code]
  • LiDAR-Flow: Dense Scene Flow Estimation from Sparse LiDAR and Stereo Images [pdf]
  • 4D Spatio-Temporal ConvNets: Minkowski Convolutional Neural Networks CVPR 2019 [pdf, code]
  • MeteorNet: Deep Learning on Dynamic 3D Point Cloud Sequences, ICCV 2019 [pdf]
  • DeepLiDARFlow: A Deep Learning Architecture For Scene Flow Estimation Using Monocular Camera and Sparse LiDAR 2020 [pdf]

Advanced Topics/Other applications

Tasks : Upsampling, Domain adaptation Sim2Real, NAS, SSL, shape reconstruction, outlier extraction, Compression, Change detection, Domain Transfer

  • Semantic Point Cloud Filtering, Masters thesis 2017 link
  • PU-GAN: a Point Cloud Upsampling Adversarial Network ICCV 2019 [pdf, code]
  • Neural Architecture Search for Object Detection in Point Cloud [blog], [AutoDeepLabNAS paper]
  • Weighted Point Cloud Augmentation for Neural Network Training Data Class-Imbalance [pdf]
  • Quantifying Data Augmentation for LiDAR based 3D Object Detection [pdf]
  • Improving 3D Object Detection through Progressive Population Based Augmentation [[pdf(]
  • 3D Object Detection From LiDAR Data Using Distance Dependent Feature Extraction VEHITS 2020 [pdf]
  • Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution ITSC 2019 [pdf]
  • Performance of LiDAR object detection deep learning architectures based on artificially generated point cloud data from CARLA simulator 2019 [pdf]
  • Efficient Learning on Point Clouds with Basis Point Sets ICCV 2019 [pdf]
  • Mastering Data Complexity for Autonomous Driving with Adaptive Point Clouds for Urban Environments 2017 [pdf]
  • Visually aided changes detection in 3D lidar based reconstruction 2015 [Thesis]
  • Fast Polar Attentive 3D Object Detection on LiDAR Point Clouds ML4AD 2021 pdf

Implicit representations

  • Neural Implicit Embedding for Point Cloud Analysis CVPR 2020 [pdf]
  • DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation [pdf]

Domain adaptation and domain transer

  • Complete & Label: A Domain Adaptation Approach to Semantic Segmentation of LiDAR Point Clouds 2020 [pdf]
  • PointDAN: A Multi-Scale 3D Domain Adaption Network for Point Cloud Representation [pdf]
  • Domain Transfer for Semantic Segmentation of LiDAR Data using Deep Neural Networks IROS 2020 [pdf, video]
  • Domain Adaptation for Vehicle Detection from Bird's Eye View LiDAR Point Cloud Data ICCVW 2019 pdf

Self-supervised learning

  • Self-Supervised Deep Learning on Point Clouds by Reconstructing Space NeurIPS 2019 [pdf]
  • SegContrast: 3D Point Cloud Feature Representation Learning RAL-ICRA'22 video, pdf
  • Self-supervised Point Cloud Prediction Using 3D Spatio-temporal CNNs CORL 2021 pdf

Graphs and Pointclouds

  • Detection of closed sharp edges in point clouds using normal estimation and graph theory CAD 2007 [link]
  • Dynamic Edge-Conditioned Filters in Convolutional Neural Networks on Graphs CVPR 2017 [pdf, vide]
  • Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs CVPR2018 [pdf]
  • ConvPoint: continuous convolutions for cloud processing Eurographics 3DOR, 2019 [pdf, code]
  • Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning [CVPR Workshop 2019], video
  • Dynamic Graph CNN for Learning on Point Clouds [pdf, project] TOG 2019

Large-scale pointcloud Algorithms (vs scan based)

  • Deep Parametric Continuous Convolutional Neural Networks CVPR 2018 [pdf]
  • PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space NeurIPS 2017 [pdf, code], semantic seg code
  • Classification of Point Cloud for Road Scene Understanding with Multiscale Voxel Deep Network Slides
  • Semantic Segmentation of 3D point Clouds Loic Landireu [Slides]
  • KPConv: Flexible and Deformable Convolution for Point Clouds [pdf, git]
  • RandLA-Net: Efficient Semantic Segmentation of Large-Scale Point Clouds [pdf, git]
  • Cylinder3D: An Effective 3D Framework for Driving-scene LiDAR Semantic Segmentation CVPR 2021 pdf

4D Panoptic LiDAR Segmentation

  • Panoptic nuScenes: A Large-Scale Benchmark for LiDAR Panoptic Segmentation and Tracking 2021 video, pdf, nuscenes benchmark
  • 4D Panoptic LiDAR Segmentation CVPR 2021 pdf, project
  • Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans 2022 RAL pdf, video

Embedded/Resource constrained pointcloud processing

  • Sparse PointPillars: Maintaining and Exploiting Input Sparsity to Improve Runtime on Embedded Systems pdf, video
  • IBB-Net: Fast Iterative Bounding Box Regression for Detection on Point Clouds, Brendan Miller, 2020 CMU masters thesis
  • Fast 3-D Urban Object Detection on Streaming Point Clouds [pdf]
  • StrObe: Streaming Object Detection from LiDAR Packets pdf, video
  • PolarStream: Streaming Lidar Object Detection and Segmentation with Polar Pillars NeurIPS 2021 pdf, video, code
  • RAD: Realtime and Accurate 3D Object Detection on Embedded Systems CVPRW 2021 pdf
  • BEVDetNet: Bird’s Eye View LiDAR Point Cloud based Real-time 3D Object Detection for Autonomous Driving ITSC 2021 pdf
  • Streaming Object Detection for 3-D Point Clouds 2020 pdf


  • Python bindings for Point Cloud Library [git]
  • Open3D [link]
  • pyntcloud [link]
  • PyVista [link]
  • torch-points3d : Pytorch framework for doing deep learning on point clouds [link]
  • Geometric Deep Learning Extension Library for [PyTorch link]
  • kaolin : A PyTorch Library for Accelerating 3D Deep Learning Research [link]
  • PyTorch3D : FAIR's library of reusable components for deep learning with 3D data [link]
  • PCDet Toolbox in PyTorch for 3D Object Detection from Point Cloud [link]
  • pointcloudset: Efficient analysis of large datasets of point clouds recorded over time [link]
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