Showing 17 open source projects for "3d point cloud processing"

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  • 1
    COLMAP

    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.
    Downloads: 70 This Week
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  • 2
    DreamCraft3D

    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. ...
    Downloads: 0 This Week
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  • 3
    CO3D (Common Objects in 3D)

    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...
    Downloads: 0 This Week
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  • 4
    UCO3D

    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...
    Downloads: 1 This Week
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  • 5
    VGGSfM

    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. ...
    Downloads: 0 This Week
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  • 6
    Edgee

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    Downloads: 14 This Week
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  • 7
    Lance

    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.
    Downloads: 3 This Week
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  • 8
    HunyuanWorld-Voyager

    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...
    Downloads: 12 This Week
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  • 9
    Jina

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    Downloads: 0 This Week
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  • 10
    Point-E

    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.
    Downloads: 0 This Week
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  • 11
    AB3DMOT

    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. ...
    Downloads: 0 This Week
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  • 12
    pyntcloud

    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.
    Downloads: 0 This Week
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  • 13
    3D-Machine-Learning

    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.
    Downloads: 0 This Week
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  • 14
    Pytorch Points 3D

    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!
    Downloads: 0 This Week
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  • 15
    Objectron

    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...
    Downloads: 0 This Week
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  • 16
    Semantic Segmentation Editor

    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.
    Downloads: 4 This Week
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  • 17
    using simple cuboids and gjk algorithm, this general purpose algorithm gives a ready made code to work with swissranger 3D camera.
    Downloads: 0 This Week
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