Point Cloud
Showing 23 of 23 projects
An open-source library for rapid development of software dealing with 3D data, with support for C++ and Python.
A standalone, large-scale open-source library for 2D/3D image and point cloud processing.
A curated repository of resources, datasets, and research papers for 3D machine learning, covering computer vision, graphics, and deep learning.
A library for compressing and decompressing 3D geometric meshes and point clouds to improve storage and transmission.
An open-source PyTorch toolbox for general 3D object detection, supporting LiDAR, camera, and multi-modal models.
An open-source, portable system for processing and editing unstructured 3D triangular meshes from 3D scanning.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A PyTorch-based toolbox for LiDAR-based 3D object detection, supporting multiple state-of-the-art models and datasets.
A free, open-source WebGL-based point cloud renderer for visualizing massive datasets directly in web browsers.
A 3D point cloud and mesh processing software for comparing, editing, and analyzing large-scale 3D data.
A C++ library with ROS interface for managing multi-layered 2D grid maps in mobile robotics.
An open specification for streaming massive heterogeneous 3D geospatial datasets across desktop, web, and mobile applications.
A ROS package for real-time 6DOF SLAM using 3D LIDAR, featuring graph-based optimization with multiple sensor constraints.
A lightweight C++ and Python viewer for 3D data like meshes and point clouds with minimal integration effort.
A robust LiDAR odometry pipeline that works out-of-the-box without parameter tuning for accurate robot localization.
A web-based labeling tool for creating semantic segmentation training data from 2D images and 3D point clouds.
An end-to-end 3D object detection network that uses deep point set networks and Hough voting to directly detect objects in point clouds.
A ROS package for extrinsic calibration between LiDAR and camera sensors using 3D-3D point correspondences.
A deep learning pipeline for 3D object detection from RGB-D data by combining 2D detectors with PointNet-based 3D processing.
A collection of high-performance GICP-based point cloud registration algorithms with multi-threaded and GPU-accelerated implementations.
A lightweight C++/Python library for 3D data processing, geometry algorithms, and rendering with an easy-to-use API.
A robust, real-time LiDAR odometry and mapping package optimized for Livox LiDARs with small fields of view.
A general-purpose PyTorch codebase for 3D object detection with state-of-the-art model implementations and multi-dataset support.
Related Tags
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.