COLMAP

About

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 reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. If you use this project for your research, please cite:

@inproceedings{schoenberger2016sfm,
    author={Sch\"{o}nberger, Johannes Lutz and Frahm, Jan-Michael},
    title={Structure-from-Motion Revisited},
    booktitle={Conference on Computer Vision and Pattern Recognition (CVPR)},
    year={2016},
}

@inproceedings{schoenberger2016mvs,
    author={Sch\"{o}nberger, Johannes Lutz and Zheng, Enliang and Pollefeys, Marc and Frahm, Jan-Michael},
    title={Pixelwise View Selection for Unstructured Multi-View Stereo},
    booktitle={European Conference on Computer Vision (ECCV)},
    year={2016},
}

If you use the image retrieval / vocabulary tree engine, please also cite:

@inproceedings{schoenberger2016vote,
    author={Sch\"{o}nberger, Johannes Lutz and Price, True and Sattler, Torsten and Frahm, Jan-Michael and Pollefeys, Marc},
    title={A Vote-and-Verify Strategy for Fast Spatial Verification in Image Retrieval},
    booktitle={Asian Conference on Computer Vision (ACCV)},
    year={2016},
}

The latest source code is available at https://github.com/colmap/colmap. COLMAP builds on top of existing works and when using specific algorithms within COLMAP, please also cite the original authors, as specified in the source code, and consider citing relevant third-party dependencies (most notably ceres-solver, poselib, sift-gpu, vlfeat).

Download

• Binaries for Windows and other resources can be downloaded from https://github.com/colmap/colmap/releases.
• Binaries for Linux/Unix/BSD are available at https://repology.org/metapackage/colmap/versions.
• Pre-built Docker images are available at https://hub.docker.com/r/colmap/colmap.
• Python bindings are available at https://pypi.org/project/pycolmap.
• To build from source, please see https://colmap.github.io/install.html.

Getting Started

1. Download pre-built binaries or build from source.
2. Download one of the provided datasets at https://demuc.de/colmap/datasets/ or use your own images.
3. Use the automatic reconstruction to easily build models with a single click or command.

Documentation

The documentation is available at https://colmap.github.io/.

Support

Please, use GitHub Discussions at https://github.com/colmap/colmap/discussions for questions and the GitHub issue tracker at https://github.com/colmap/colmap for bug reports, feature requests/additions, etc.

Acknowledgments

COLMAP was originally written by Johannes Schönberger with funding provided by his PhD advisors Jan-Michael Frahm and Marc Pollefeys.

The Python bindings in PyCOLMAP were originally added by Mihai Dusmanu, Philipp Lindenberger, and Paul-Edouard Sarlin.

The project has also benefitted from countless community contributions, including bug fixes, improvements, new features, third-party tooling, and community support (special credits to Torsten Sattler).

Contribution

Contributions (bug reports, bug fixes, improvements, etc.) are very welcome and should be submitted in the form of new issues and/or pull requests on GitHub.

License

The COLMAP library is licensed under the new BSD license. Note that this text refers only to the license for COLMAP itself, independent of its thirdparty dependencies, which are separately licensed. Building COLMAP with these dependencies may affect the resulting COLMAP license.

Copyright (c) 2023, ETH Zurich and UNC Chapel Hill.
All rights reserved.

Redistribution and use in source and binary forms, with or without
modification, are permitted provided that the following conditions are met:

    * Redistributions of source code must retain the above copyright
      notice, this list of conditions and the following disclaimer.

    * Redistributions in binary form must reproduce the above copyright
      notice, this list of conditions and the following disclaimer in the
      documentation and/or other materials provided with the distribution.

    * Neither the name of ETH Zurich and UNC Chapel Hill nor the names of
      its contributors may be used to endorse or promote products derived
      from this software without specific prior written permission.

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