Lidar Point clound processing for Autonomous Driving
A list of references on lidar point cloud processing for autonomous driving
LiDAR Pointcloud Clustering/Semantic Segmentation
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 [
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
-
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
]
Continous domain DNNs
-
Deep Parametric Continuous Convolutional Neural Networks CVPR 2018 [
pdf
]
Pointcloud Density
-
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
]
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
] -
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
]
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
]
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
]
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
] -
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
] -
A*3D: An Autonomous Driving Dataset in Challeging Environments [
dataset
], [
video
]
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
]
Advanced Topics/Other applications
TAsks
: Upsampling, Domain adaptation Sim2Real, NAS, SSL
-
PU-GAN: a Point Cloud Upsampling Adversarial Network ICCV 2019 [
pdf
,
code
] -
Neural Architecture Search for Object Detection in Point Cloud [
blog
], [
AutoDeepLabNAS paper
] -
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space NeurIPS 2019 [
pdf
] -
Domain Adaptation for Vehicle Detection from Bird’s Eye View LiDAR Point Cloud Data ICCVW 2019
pdf
-
Weighted Point Cloud Augmentation for Neural Network Training Data Class-Imbalance [
pdf
]
Large-scale pointcloud Algorithms (vs scan based)
- Datasets :
-
Large-scale Point Cloud Semantic Segmentation with Superpoint Graphs CVPR2018 [
pdf
] -
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space NeurIPS 2017 [
pdf
,
code
],
semantic seg code
-
ConvPoint: continuous convolutions for cloud processing Eurographics 3DOR, 2019
pdf
,
code
-
Classification of Point Cloud for Road Scene Understanding with Multiscale Voxel Deep Network
Slides
-
Semantic Segmentation of 3D point Clouds Loic Landireu [
Slides
] -
Point Cloud Oversegmentation with Graph-Structured Deep Metric Learning [
CVPR Workshop 2019
],
video
Tools/SW/Packages