Patchwork++: Fast and robust ground segmentation method for 3D LiDAR scans. @ IROS'22

SOTA fast and robust ground segmentation using 3D point cloud (accepted in RA-L'21 w/ IROS'21)

ROS & ROS2 Implementation of Patchwork++

Ground segmentation benchmark in SemanticKITTI dataset

GndNet: Fast ground plane estimation and point cloud segmentation for autonomous vehicles using deep neural networks.

Efficient Online Segmentation of Ground&Wall Points for Multi-line Spinning LiDARs. //在线分割激光点云中的地面点和墙面点。

Source code for the article "GroundGrid: LiDAR Point Cloud Ground Segmentation and Terrain Estimation"

点云分割论文2017 Fast segmentation of 3d point clouds: A paradigm on lidar data for autonomous vehicle applications

A ground segmentation algorithm for 3D point clouds based on the work described in “Fast segmentation of 3D point clouds: a paradigm on LIDAR data for Autonomous Vehicle Applications”, D. Zermas, I. Izzat and N. Papanikolopoulos, 2017. Distinguish between road and non-road points. Road surface extraction. Plane fit ground filter

An implementation on "Shen Z, Liang H, Lin L, Wang Z, Huang W, Yu J. Fast Ground Segmentation for 3D LiDAR Point Cloud Based on Jump-Convolution-Process. Remote Sensing. 2021; 13(16):3239. https://doi.org/10.3390/rs13163239"

快速3D点云分割论文代码（带注解）：Fast segmentation of 3d point clouds for ground vehicles

A C++ version for "A Slope-robust Cascaded Ground Segmentation in 3D Point Cloud for Autonomous Vehicles" 2018 ITSC

Ground Segmentation Package in ROS.

Python Package: Fast Ground Segmentation for LiDAR Point Clouds

Pointcloud Ground Segmentation: python binding of url-kaist/TRAVEL

Segmentation of a video frame into ground and upright objects using sparse and dense optical flow techniques in OpenCV.

Pure Python Libary of Ground Segmentation Algorithms

ROS2 Implementation of Patchwork

ROS2 Implementation of Patchwork++