Search Results for "3d point cloud processing"
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Showing 40 open source projects for "3d point cloud processing"
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CloudCompare
CloudCompare main repository
CloudCompare is a 3D point cloud (and triangular mesh) processing software. It was originally designed to perform comparison between two 3D points clouds (such as the ones obtained with a laser scanner) or between a point cloud and a triangular mesh. It relies on an octree structure that is highly optimized for this particular use-case. It was also meant to deal with huge point clouds (typically more than 10 million points, and up to 120 million with 2 GB of memory). -
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COLMAP
Structure-from-Motion and Multi-View Stereo
COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for the reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. -
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DreamCraft3D
Official implementation of DreamCraft3D
DreamCraft3D is DeepSeek’s generative 3D modeling framework / model family that likely extends their earlier 3D efforts (e.g. Shap-E or Point-E style models) with more capability, control, or expression. The name suggests a “dream crafting” metaphor—users probably supply textual or image prompts and generate 3D assets (point clouds, meshes, scenes). The repository includes model code, inference scripts, sample prompts, and possibly dataset preparation pipelines. ... -
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Easy3D
Efficient library for processing 3D data
Easy3D is a lightweight, easy-to-use, and efficient library for processing and rendering 3D data, implemented in C++ with Python bindings. It is designed for tasks such as 3D modeling, geometry processing, and rendering, emphasizing simplicity and efficiency. Easy3D serves as a valuable tool for research, education, and the development of sophisticated 3D applications, providing a solid foundation for handling 3D data. -
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Open3D
A modern library for 3D data processing
Open3D is an open-source library that supports rapid development of software that deals with 3D data. The Open3D frontend exposes a set of carefully selected data structures and algorithms in both C++ and Python. The backend is highly optimized and is set up for parallelization. Open3D was developed from a clean slate with a small and carefully considered set of dependencies. It can be set up on different platforms and compiled from source with minimal effort. The code is clean, consistently... -
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Discontinuity Set Extractor (DSE) is programmed by Adrián Riquelme for testing part of his PdD studies. Its aim is to extract discontinuity sets from a rock mass. The input data is a 3D point cloud, which can be acquired by means of a 3D laser scanner (LiDAR or TLS), digital photogrammetry techniques (such as SfM) or synthetic data. It applies a proposed methodology to semi-automatically identify points members of an unorganised 3D point cloud that are arranged in 3D space by planes.
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
CO3Dv2 (Common Objects in 3D, version 2) is a large-scale 3D computer vision dataset and toolkit from Facebook Research designed for training and evaluating category-level 3D reconstruction methods using real-world data. It builds upon the original CO3Dv1 dataset, expanding both scale and quality—featuring 2× more sequences and 4× more frames, with improved image fidelity, more accurate segmentation masks, and enhanced annotations for object-centric 3D reconstruction. CO3Dv2 enables research... -
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VGGSfM
VGGSfM: Visual Geometry Grounded Deep Structure From Motion
VGGSfM is an advanced structure-from-motion (SfM) framework jointly developed by Meta AI Research (GenAI) and the University of Oxford’s Visual Geometry Group (VGG). It reconstructs 3D geometry, dense depth, and camera poses directly from unordered or sequential images and videos. The system combines learned feature matching and geometric optimization to generate high-quality camera calibrations, sparse/dense point clouds, and depth maps in standard COLMAP format. Version 2.0 adds support for dynamic scene handling, dense point cloud export, video-based reconstruction (1000+ frames), and integration with Gaussian Splatting pipelines. ... -
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Lance
Modern columnar data format for ML and LLMs implemented in Rust
Lance is a columnar data format that is easy and fast to version, query and train on. It’s designed to be used with images, videos, 3D point clouds, audio and of course tabular data. It supports any POSIX file systems, and cloud storage like AWS S3 and Google Cloud Storage. -
See what everyone is allocated to. Projects, clients, meetings - all in one tool.Designed to replace clunky, old scheduling spreadsheets, Resource Guru helps managers get organized fast. The platform covers resource planning, resource scheduling, resource management, staff leave management, reporting, and more.
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UCO3D
Uncommon Objects in 3D dataset
uCO3D is a large-scale 3D vision dataset and toolkit centered on turn-table videos of everyday objects drawn from the LVIS taxonomy. It provides about 170,000 full videos per object instance rather than still frames, along with per-video annotations including object masks, calibrated camera poses, and multiple flavors of point clouds. Each sequence also ships with a precomputed 3D Gaussian Splat reconstruction, enabling fast, differentiable rendering workflows and modern implicit/point-based... -
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Edgee
AI gateway with token compression for Claude Code, Codex, and more
Edgee is an edge-native execution platform designed to run AI-driven logic and data processing directly at the network edge, reducing latency and improving responsiveness for modern applications. It enables developers to deploy functions and workflows closer to users, allowing real-time processing without relying heavily on centralized cloud infrastructure. The platform is built to support event-driven architectures, where actions are triggered by incoming requests, user behavior, or external signals. ... -
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HunyuanWorld-Voyager
RGBD video generation model conditioned on camera input
HunyuanWorld-Voyager is a next-generation video diffusion framework developed by Tencent-Hunyuan for generating world-consistent 3D scene videos from a single input image. By leveraging user-defined camera paths, it enables immersive scene exploration and supports controllable video synthesis with high realism. The system jointly produces aligned RGB and depth video sequences, making it directly applicable to 3D reconstruction tasks. At its core, Voyager integrates a world-consistent video... -
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Jina
Build cross-modal and multimodal applications on the cloud
Jina is a framework that empowers anyone to build cross-modal and multi-modal applications on the cloud. It uplifts a PoC into a production-ready service. Jina handles the infrastructure complexity, making advanced solution engineering and cloud-native technologies accessible to every developer. Build applications that deliver fresh insights from multiple data types such as text, image, audio, video, 3D mesh, PDF with Jina AI’s DocArray. Polyglot gateway that supports gRPC, Websockets, HTTP,... -
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gl
Windowless WebGL for node.js
headless-gl is an open-source Node.js library that provides a WebGL rendering context without requiring a browser window or graphical user interface. It enables developers to create and manipulate WebGL contexts directly within server-side JavaScript environments, making it possible to perform GPU-accelerated rendering tasks without launching a full browser. The project aims to conform closely to the WebGL specification so that standard WebGL APIs and shaders can be used in Node.js... -
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Openbravopos
Open Source Openbravo POS convert to Commercial Retail ERP and POS
Complete and user-friendly retail POS functionality A comprehensive, flexible, and user-friendly cloud-based retail POS software. 1. Sales, quotations, reservations, and returns, including cross-store and cross-channel scenarios. 2. Automatic validation of customer personal data. 3. Configuration of keymaps for quick access to options and featured products. https://www.youtube.com/watch?v=Aai3iYLP2TQ&pp=ygUNb3BlbmJyYXZvIGtkcw%3D%3D Contact: both version of Openbravo POS... -
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LPub3D
LDraw™ editor for LEGO® style digital building instructions.
LPub3D is an Open Source WYSIWYG editing application for creating LEGO® style digital building instructions. LPub3D is developed and maintained by Trevor SANDY. It uses the LDraw™ parts library, the most comprehensive library of digital Open Source LEGO® bricks available (www.ldraw.org/ ) and reads the LDraw LDR and MPD model file formats. LPub3D is available for free under the GNU Public License v3 and runs on Windows, Linux and macOS Operating Systems. LPub3D is also... -
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Point-E
Point cloud diffusion for 3D model synthesis
point-e is the official repository for Point-E, a generative model developed by OpenAI that produces 3D point clouds from textual (or image) prompts. Its principal advantage is speed: it can generate 3D assets in just 1–2 minutes on a single GPU, which is significantly faster than many competing text-to-3D models. The model works via a two-stage diffusion approach: first, it uses a text → image diffusion network to produce a synthetic 2D view consistent with the prompt; then a second diffusion model converts that image into a 3D point cloud. -
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AB3DMOT
Official Python Implementation for "3D Multi-Object Tracking
AB3DMOT is a real-time 3D multi-object tracking framework designed for applications such as autonomous driving and robotics perception. The system processes detection results from 3D object detectors that analyze LiDAR point clouds and uses them to track multiple objects across consecutive frames. Its tracking pipeline relies on a combination of classical algorithms, including a Kalman filter for state estimation and the Hungarian algorithm for data association between detected objects and existing tracks. ... -
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pyntcloud
pyntcloud is a Python library for working with 3D point clouds
...Accurate 3D point clouds can nowadays be (easily and cheaply) acquired from different sources. pyntcloud enables simple and interactive exploration of point cloud data, regardless of which sensor was used to generate it or what the use case is. Although it was built for being used on Jupyter Notebooks, the library is suitable for other kinds of uses. pyntcloud is composed of several modules (as independent as possible) that englobe common point cloud processing operations. -
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3D-Machine-Learning
A resource repository for 3D machine learning
...The repository includes references to important research papers covering topics such as point cloud processing, 3D reconstruction, shape analysis, and scene understanding. It also organizes links to university courses and other educational materials that explore machine learning methods for 3D data. Because the field is evolving rapidly, the repository functions as a continuously expanding knowledge base for researchers and developers studying 3D perception systems. -
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Pytorch Points 3D
Pytorch framework for doing deep learning on point clouds
Torch Points 3D is a framework for developing and testing common deep learning models to solve tasks related to unstructured 3D spatial data i.e. Point Clouds. The framework currently integrates some of the best-published architectures and it integrates the most common public datasets for ease of reproducibility. It heavily relies on Pytorch Geometric and Facebook Hydra library thanks for the great work! -
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Objectron
A dataset of short, object-centric video clips
The Objectron dataset is a collection of short, object-centric video clips, which are accompanied by AR session metadata that includes camera poses, sparse point-clouds and characterization of the planar surfaces in the surrounding environment. In each video, the camera moves around the object, capturing it from different angles. The data also contain manually annotated 3D bounding boxes for each object, which describe the object’s position, orientation, and dimensions. The dataset consists... -
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Semantic Segmentation Editor
Web labeling tool for bitmap images and point clouds
A web-based labeling tool for creating AI training data sets (2D and 3D). The tool has been developed in the context of autonomous driving research. It supports images (.jpg or .png) and point clouds (.pcd). It is a Meteor app developed with React, Paper.js, and three.js. -
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PyMesh
Geometry processing library for Python
PyMesh is a codebase developed by Qingnan Zhou for his PhD research at New York University. It is a rapid prototyping platform focused on geometry processing. PyMesh is written with both C++ and Python, where computational intensive functionalities are realized in C++, and Python is used for creating minimalistic and easy-to-use interfaces. PyMesh is a rapid prototyping platform focused on geometry processing. It provides a set of common mesh processing functionalities and interfaces with a... -
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Dynamic Robot Localization
Point cloud registration pipeline for robot localization and 3D
...It's a modular localization pipeline, that can be configured using yaml files (detailed configuration layout available in drl_configs.yaml and examples of configurations available in guardian_config and dynamic_robot_localization_tests). Even though this package was developed for robot self-localization and mapping, it was implemented as a generic, configurable and extensible point cloud matching library, allowing its usage in related problems such as estimation of the 6 DoF pose of an object and 3D object scanning.
