A list of references on lidar point cloud processing for autonomous driving
- 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]
- An Improved RANSAC for 3D Point Cloud Plane Segmentation Based on Normal Distribution Transformation Cells
- Fast semantic segmentation of 3d point clounds with strongly varying density [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]
- Point Clouds Registration with Probabilistic Data Association [git]
- Robust LIDAR Localization using Multiresolution Gaussian Mixture Maps for Autonomous Driving [pdf]
- Automatic Merging of Lidar Point-Clouds Using Data from Low-Cost GPS/IMU Systems [pdf]
- 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]
- 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
- 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]
- Fast LIDAR-based Road Detection Using Fully Convolutional Neural Networks [pdf]
- ChipNet: Real-Time LiDAR Processing for Drivable Region Segmentation on an FPGA [pdf]
- LIDAR-Data Accumulation Strategy To Generate High Definition Maps For Autonomous Vehicles [link]
- 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]
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