{"id":4567,"url":"https://github.com/mmolero/awesome-point-cloud-processing","name":"awesome-point-cloud-processing","description":"A curated list of awesome Point Cloud Processing Resources, Libraries, Software","projects_count":39,"last_synced_at":"2026-05-30T01:00:22.991Z","repository":{"id":2961601,"uuid":"45192673","full_name":"mmolero/awesome-point-cloud-processing","owner":"mmolero","description":"A curated list of awesome Point Cloud Processing Resources, Libraries, Software","archived":false,"fork":false,"pushed_at":"2025-11-27T07:24:07.000Z","size":3048,"stargazers_count":798,"open_issues_count":2,"forks_count":135,"subscribers_count":45,"default_branch":"master","last_synced_at":"2026-05-13T10:02:34.173Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"cc0-1.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/mmolero.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2015-10-29T15:34:59.000Z","updated_at":"2026-04-20T06:10:20.000Z","dependencies_parsed_at":"2022-07-31T23:39:04.098Z","dependency_job_id":null,"html_url":"https://github.com/mmolero/awesome-point-cloud-processing","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mmolero/awesome-point-cloud-processing","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mmolero%2Fawesome-point-cloud-processing","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mmolero%2Fawesome-point-cloud-processing/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mmolero%2Fawesome-point-cloud-processing/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mmolero%2Fawesome-point-cloud-processing/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mmolero","download_url":"https://codeload.github.com/mmolero/awesome-point-cloud-processing/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mmolero%2Fawesome-point-cloud-processing/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":33676191,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-05-29T02:00:06.066Z","response_time":107,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"created_at":"2024-01-06T20:24:58.981Z","updated_at":"2026-05-30T01:00:22.993Z","primary_language":null,"list_of_lists":false,"displayable":true,"categories":["Libraries","Tutorials","Software (Open Source)","Conferences","Community","Papers","News","Web-based point cloud viewers","Servers"],"sub_categories":[],"readme":"# awesome-point-cloud-processing\n\nA curated list of awesome Point Cloud Processing Resources, Libraries, Software. Inspired by [awesome-machine-learning](https://github.com/josephmisiti/awesome-machine-learning)\n\n**Please feel free to add more resources (pull requests)**\n\n\n## Tutorials\n\n[Data Structures for Large 3D Point Cloud Processing](http://www7.informatik.uni-wuerzburg.de/mitarbeiter/nuechter/tutorial2014). Data Structures for Large 3D Point Cloud Processing Tutorial at the 13th International Conference on Intelligent Autonomous Systems\n\n[INF555 Geometric Modeling: Digital Representation\nand Analysis of Shapes: lecture 7](http://www.enseignement.polytechnique.fr/informatique/INF555/Slides/lecture7.pdf). \n\n[3D Deep Learning on Point Cloud Data](http://graphics.stanford.edu/courses/cs468-17-spring/LectureSlides/L16%20-%203d%20deep%20learning%20on%20point%20cloud%20(analysis)%20and%20joint%20embedding.pdf)\n\n## Libraries\n\n- [**PCL - Point Cloud Library**](http://pointclouds.org/) is a standalone, large scale, open project for 2D/3D image and point cloud processing.\n- [**3DTK - The 3D Toolkit**](http://slam6d.sourceforge.net/) provides algorithms and methods to process 3D point clouds.\n- [**PDAL - Point Data Abstraction Library**](http://www.pdal.io/) is a C++/Python BSD library for translating and manipulating point cloud data.\n- [**libLAS**](http://liblas.org/) is a C/C++ library for reading and writing the very common LAS LiDAR format (Legacy. Replaced by PDAL).\n- [**entwine**](https://github.com/connormanning/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.\n- [**PotreeConverter**](https://github.com/potree/PotreeConverter) is another data organisation library, generating data for use in the Potree web viewer.\n- [**lidR**](https://github.com/Jean-Romain/lidR) R package for Airborne LiDAR Data Manipulation and Visualization for Forestry Applications. \n- [**pypcd**](https://github.com/dimatura/pypcd) Python module to read and write point clouds stored in the PCD file format, used by the Point Cloud Library.\n- [**Open3D**](https://github.com/intel-isl/Open3D) is an open-source library that supports rapid development of software that deals with 3D data. It has Python and C++ frontends.\n- [**cilantro**](https://github.com/kzampog/cilantro) A Lean and Efficient Library for Point Cloud Data Processing (C++).\n- [**PyVista**](https://github.com/pyvista/pyvista/) 3D plotting and mesh analysis through a streamlined interface for the Visualization Toolkit(VTK).\n- [**pyntcloud**](https://github.com/daavoo/pyntcloud) is a Python library for working with 3D point clouds.\n- [**pylas**](https://github.com/tmontaigu/pylas) Reading Las (lidar) in Python.\n- [**PyTorch**](https://github.com/rusty1s/pytorch_geometric) PyTorch Geometric (PyG) is a geometric deep learning extension library for PyTorch.\n\n## Software (Open Source)\n\n- [**Paraview**](http://www.paraview.org/). Open-source, multi-platform data analysis and visualization application. \n- [**MeshLab**](http://meshlab.sourceforge.net/). Open source, portable, and extensible system for the processing and editing of unstructured 3D triangular meshes\n- [**CloudCompare**](https://cloudcompare.org/). 3D point cloud and mesh processing software \nOpen Source Project\n- [**OpenFlipper**](http://www.openflipper.org/). An Open Source Geometry Processing and Rendering Framework\n- [**PotreeDesktop**](https://github.com/potree/PotreeDesktop). A desktop/portable version of the web-based point cloud viewer [**Potree**](https://github.com/potree/potree)\n- [**3d-annotation-tool**](https://github.com/StrayRobots/3d-annotation-tool). A lightweight desktop application to annotate pointclouds for machine learning.\n\n## Servers\n\n- [**LOPoCS**](https://oslandia.github.io/lopocs/) is a point cloud server written in Python\n- [**Greyhound**](https://github.com/hobu/greyhound) is a server designed to deliver points from Entwine octrees\n\n## Web-based point cloud viewers\n\n- [**Potree**](https://github.com/potree/potree) is a web-based octree viewer written in Javascript.\n\n## Conferences\n\n- [**International LiDAR Mapping Forum**](https://www.lidarmap.org/) International LiDAR Mapping Forum (ILMF)\n- [**3D-ARCH**](http://www.3d-arch.org/) 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.\n- [**Geo Business**](https://www.geobusinessshow.com/programme/) Geospatial event with many 3D Point clound and LiDAR presentations.\n- [**LiDAR Comex**](https://lidarcomex.com/) The Lidar Commercial Expo.\n\n## Community\n\n- [**Laser Scanning Forum**](https://www.laserscanningforum.com/forum/) Laser Scanning Forum\n- [**PCL Discord**](https://discord.com/invite/JFFMAXS) Point Cloud Library (PCL) Discord channel.\n\n## Papers \n\n[awesome-point-cloud-analysis](https://github.com/Yochengliu/awesome-point-cloud-analysis) for anyone who wants to do research about 3D point cloud.\n\n[Efficient Processing of Large 3D Point Clouds](https://www.researchgate.net/publication/233792575_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 \n\n[Data Structure for Efficient Processing in 3-D](http://www.roboticsproceedings.org/rss01/p48.pdf) Jean-François Lalonde, Nicolas Vandapel and Martial Hebert, Robotics: Science and Systems I, 2005\n\n[An out-of-core octree for massive point cloud processing](http://rs.tudelft.nl/~rlindenbergh/workshop/WenzelIQmulus.pdf) K. Wenzel, M. Rothermel, D. Fritsch, N. Haala, Workshop on Processing Large Geospatial Data 2014\n\n## News\n\n[LiDAR News](https://lidarnews.com/) About 3D laser scanning and lidar, along with a number of related technologies such as unmanned aerial systems – UASs and photogrammetry. \n\n[LiDAR Mag](https://lidarmag.com/) Magazine about LiDARs.\n\n[Wired](https://www.wired.com/tag/lidar/) The WIRED conversation illuminates how technology is changing every aspect of our lives—from culture to business, science to design.\n\n[GIM International](https://www.gim-international.com/news/lidar) GIM International is the independent and high-quality information source for everything the global geomatics industry has to offer.\n","projects_url":"https://awesome.ecosyste.ms/api/v1/lists/mmolero%2Fawesome-point-cloud-processing/projects"}