958207985 / lidar_for_ad_references

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

Lidar Point clound processing for Autonomous Driving

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

Clustering/Segmentation (road/ground extraction, plane extraction)

• Fast Segmentation of 3D Point Clouds: A Paradigm on LiDAR Data for Autonomous Vehicle Applications [git]
• 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 [pdf]
• Fast Multi-pass 3D Point Segmentation Based on a Structured Mesh Graph for Ground Vehicles pdf video
• Circular Convolutional Neural Networks for Panoramic Images and Laser Data pdf
• Python bindings for Point Cloud Library [git]

Pointcloud Density

• DBSCAN algorithm : wiki, A density-based algorithm for discovering clusters in large spatial databases with noise (1996) [pdf[(https://www.aaai.org/Papers/KDD/1996/KDD96-037.pdf)
• Hierarchical Density Estimates for Data Clustering, Visualization, and Outlier Detection 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]

Registration and Localization

• Point Clouds Registration with Probabilistic Data Association [git]
• Robust LIDAR Localization using Multiresolution Gaussian Mixture Maps for Autonomous Driving [pdf], [Thesis]
• Automatic Merging of Lidar Point-Clouds Using Data from Low-Cost GPS/IMU Systems [pdf]
• 3DFeat-Net: Weakly Supervised Local 3D Features for Point Cloud Registration [pdf]
• Incremental Segment-Based Localization in 3D Point Clouds [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]

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]
• 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

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 3D map maintenance in dynamic environments [video]
• Detection and Tracking of Moving Objects Using 2.5D Motion Grids [pdf]
• 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]
• Fast 3-D Urban Object Detection on Streaming Point Clouds [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]

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]

Lidar Datasets and Simulators

• nuScenes : public large-scale dataset for autonomous driving [dataset]
• Paris-Lille-3D: A Point Cloud Dataset for Urban Scene Segmentation and Classification [pdf dataset]
• A LiDAR Point Cloud Generator: from a Virtual World to Autonomous Driving pdf
• Ford Campus Vision and Lidar Data Set pdf dataset
• Oxford RobotCar dataset dataset 1 Year, 1000km: The Oxford RobotCar Dataset pdf
• Udacity based simulator [link, git]
• Tutorial on Gazebo to simulate raycasting from Velodyne lidar [link]
• Udacity Driving Dataset [link]
• Virtual KITTI [link]
• LiDAR-Video Driving Dataset: Learning Driving Policies Effectively [pdf]
• KAIST Complex Urban Data Set Dataset [dataset]
• Semantic KITTI [dataset]

Movement and flow estimation in Pointclouds

• 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