A point cloud is a set of data points in space. The points represent a 3D shape or object. Each point has its set of X, Y and Z coordinates.
A resource repository for 3D machine learning
Point Cloud Library (PCL)
Draco is a library for compressing and decompressing 3D geometric meshes and point clouds. It is intended to improve the storage and transmission of 3D graphics.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images.
The public CGAL repository, see the README below
The open source mesh processing system
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
OpenMMLab's next-generation platform for general 3D object detection.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
open Multi-View Stereo reconstruction library
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
User-friendly, commercial-grade software for processing aerial imagery.
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
Pytorch framework for doing deep learning on point clouds.
Specification for streaming massive heterogeneous 3D geospatial datasets
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
Deep Hough Voting for 3D Object Detection in Point Clouds