Point Cloud Segmentation
Showing 7 of 7 projects
A curated list of papers, datasets, and code for 3D point cloud analysis research, covering classification, segmentation, detection, and more.
Fast and robust algorithm for segmenting Velodyne LiDAR point clouds into objects for autonomous driving applications.
A C++ library for fast ground segmentation from LiDAR point clouds using the line-fit algorithm.
A PyTorch framework for semantic segmentation of large 3D point clouds using superpoint graphs.
A ROS library for LiDAR point cloud segmentation, enabling ground removal and object clustering for autonomous vehicle perception.
A real-time ROS 2 package for detecting drivable roads and sidewalks from LIDAR point clouds in urban autonomous driving scenarios.
An algorithm for optimal worst-case instance segmentation of LiDAR point clouds using objectness scoring.
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.