A curated list of awesome Point Cloud Processing Resources, Libraries, Software. Inspired by awesome-machine-learning

Please feel free to add more resources (pull requests)

Data Structures for Large 3D Point Cloud Processing. Data Structures for Large 3D Point Cloud Processing Tutorial at the 13th International Conference on Intelligent Autonomous Systems

INF555 Geometric Modeling: Digital Representation and Analysis of Shapes: lecture 7.

3D Deep Learning on Point Cloud Data

• PCL - Point Cloud Library is a standalone, large scale, open project for 2D/3D image and point cloud processing.
• 3DTK - The 3D Toolkit provides algorithms and methods to process 3D point clouds.
• PDAL - Point Data Abstraction Library is a C++ BSD library for translating and manipulating point cloud data.
• libLAS is a C/C++ library for reading and writing the very common LAS LiDAR format.
• entwine is a data organization library for massive point clouds, designed to conquer datasets of hundreds of billions of points as well as desktop-scale point clouds.
• PotreeConverter is another data organisation library, generating data for use in the Potree web viewer.
• lidR R package for Airborne LiDAR Data Manipulation and Visualization for Forestry Applications.

• Paraview. Open-source, multi-platform data analysis and visualization application.
• MeshLab. Open source, portable, and extensible system for the processing and editing of unstructured 3D triangular meshes
• CloudCompare. 3D point cloud and mesh processing software Open Source Project
• OpenFlipper. An Open Source Geometry Processing and Rendering Framework
• PotreeDesktop. A desktop/portable version of the web-based point cloud viewer Potree

• LOPoCS is a point cloud server written in Python
• Greyhound is a server designed to deliver points from Entwine octrees

• Potree is a web-based octree viewer written in Javascript.

• International LiDAR Mapping Forum International LiDAR Mapping Forum (ILMF)
• 3D-ARCH is a series of international workshops to discuss steps and processes for smart 3D reconstruction, modelling, accessing and understanding of digital environments from multiple data sources.

• Laser Scanning Forum Laser Scanning Forum

Efficient Processing of Large 3D Point Clouds Jan Elseberg, Dorit Borrmann, Andreas N̈uchtre, Proceedings of the XXIII International Symposium on Information, Communication and Automation Technologies (ICAT '11), 2011

Data Structure for Efficient Processing in 3-D Jean-François Lalonde, Nicolas Vandapel and Martial Hebert, Robotics: Science and Systems I, 2005

An out-of-core octree for massive point cloud processing K. Wenzel, M. Rothermel, D. Fritsch, N. Haala, Workshop on Processing Large Geospatial Data 2014