Point Cloud
Showing 36 of 88 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 robust LiDAR odometry pipeline that works out-of-the-box without parameter tuning for accurate robot localization.
A lightweight C++ and Python viewer for 3D data like meshes and point clouds with minimal integration effort.
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.
A Unity package for importing and rendering point cloud data with support for PLY files and multiple rendering methods.
A deep learning framework for feature learning directly from point clouds using X-Conv operations, achieving state-of-the-art results in classification and segmentation.
Fast and robust algorithm for segmenting Velodyne LiDAR point clouds into objects for autonomous driving applications.
A curated list of awesome LIDAR sensors, datasets, libraries, algorithms, and simulators for robotics and autonomous driving.
A curated list of awesome LIDAR sensors, datasets, libraries, algorithms, frameworks, and simulators for robotics and autonomous driving.
A curated collection of papers, toolboxes, and notes for LiDAR-camera extrinsic calibration methods.
Python tools for working with the KITTI autonomous driving dataset, providing data loaders and utilities for computer vision and robotics.
Fast and optimized LiDAR odometry and mapping for real-time indoor/outdoor robot localization, achieving up to 3x speedup over prior methods.
A lean and fast C++ library for 3D point cloud data processing with efficient implementations of common operations.
A 3D segment-based mapping library for robot localization, environment reconstruction, and semantics extraction using LiDAR data.
A Blender addon for visualizing, editing, filtering, rendering, and converting point cloud PLY files within the 3D viewport.
Award-winning, efficient C++ tools for processing LiDAR data in LAS/LAZ formats with multi-core batch processing.
A CUDA-accelerated library for rapid 3D data processing in robotics, enabling GPU-powered SLAM, collision avoidance, and path planning.
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.