Showing 1-20 of 46 projects
Point Cloud Library (PCL) is a powerful open-source library for 3D computer vision and point cloud processing.
A comprehensive repository of resources for 3D machine learning, including papers, datasets, and frameworks.
Draco is a C++ library for compressing and decompressing 3D geometric meshes and point clouds.
A command-line toolkit to generate maps, point clouds, 3D models and DEMs from drone, balloon or kite images.
CGAL is a C++ library providing a wide range of advanced algorithms and data structures for computational geometry and geometric processing.
An open-source mesh processing system for 3D modeling, reconstruction, and editing.
A toolbox for 3D object detection using LiDAR point clouds, focused on autonomous driving use cases.
PointNet is a deep learning model for 3D classification and segmentation on point cloud data.
PyTorch implementation of PointNet and PointNet++ for 3D point cloud classification and segmentation.
CloudCompare is a powerful 3D point cloud processing and visualization tool, primarily used for 3D data analysis.
openMVS is a C++ library for 3D reconstruction from multi-view stereo images.
A curated list of tools for professional robotic development in C++ and Python with ROS, autonomous driving, and aerospace.
An open-source, user-friendly software for processing aerial imagery and creating 3D maps and point clouds.
Deep learning library for point clouds in 3D space
A BVH implementation to speed up raycasting and enable spatial queries against three.js meshes.
A comprehensive collection of papers and datasets for 3D point cloud processing, useful for developers working on autonomous driving and computer vision.
Pointcept is a codebase for point cloud perception research, featuring the latest works on 3D computer vision.
A PyTorch framework for deep learning on point clouds, with support for various point cloud-related tasks.
A C++11 header-only library for Nearest Neighbor search with KD-trees
Specification for streaming massive heterogeneous 3D geospatial datasets across the web.
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