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Point cloud
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
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.
OpenMMLab's next-generation platform for general 3D object detection.
The public CGAL repository, see the README below
A command line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images. 📷
The open source mesh processing system
OpenPCDet Toolbox for LiDAR-based 3D Object Detection.
PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation
PointNet and PointNet++ implemented by pytorch (pure python) and on ModelNet, ShapeNet and S3DIS.
open Multi-View Stereo reconstruction library
Tooling for professional robotic development in C++ and Python with a touch of ROS, autonomous driving and aerospace.
PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
User-friendly, commercial-grade software for processing aerial imagery. ✈️
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
Papers and Datasets about Point Cloud.
Pytorch framework for doing deep learning on point clouds.
Pointcept: Perceive the world with sparse points, a codebase for point cloud perception research. Latest works: Sonata (CVPR'25 Highlight), PTv3 (CVPR'24 Oral)
📚 The list of vision-based SLAM / Visual Odometry open source, blogs, and papers