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COLMAP
======
.. figure:: images/sparse.png
:alt: Sparse reconstruction of central Rome.
:figclass: align-center
Sparse model of central Rome using 21K photos produced by COLMAP's SfM
pipeline.
.. figure:: images/dense.png
:alt: Dense reconstruction of landmarks.
:figclass: align-center
Dense models of several landmarks produced by COLMAP's MVS pipeline.
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.
The latest source code is available at `GitHub
<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.
Download
--------
Executables and other resources can be downloaded from https://demuc.de/colmap/.
Getting Started
---------------
1. Download the `pre-built binaries <https://demuc.de/colmap/>`_ or build the
library manually from `source <https://github.com/colmap/colmap>`_
(see :ref:`Installation <installation>`).
2. Download one of the provided datasets (see :ref:`Datasets <datasets>`)
or use your own images.
3. Use the **automatic reconstruction** to easily build models
with a single click (see :ref:`Quickstart <quick-start>`).
Support
-------
Please, use `GitHub Discussions <https://github.com/colmap/colmap/discussions>`_
for questions and the `GitHub issue tracker <https://github.com/colmap/colmap>`_
for bug reports, feature requests/additions, etc.
Citation
--------
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 global SfM pipeline (GLOMAP), please cite::
@inproceedings{pan2024glomap,
author={Pan, Linfei and Barath, Daniel and Pollefeys, Marc and Sch\"{o}nberger, Johannes Lutz},
title={{Global Structure-from-Motion Revisited}},
booktitle={European Conference on Computer Vision (ECCV)},
year={2024},
}
If you use the image retrieval / vocabulary tree engine, please 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},
}
Acknowledgments
---------------
COLMAP was originally written by `Johannes Schönberger <https://demuc.de/>`__ with
funding provided by his PhD advisors Jan-Michael Frahm and Marc Pollefeys.
The team of core project maintainers currently includes
`Johannes Schönberger <https://github.com/ahojnnes>`__,
`Paul-Edouard Sarlin <https://github.com/sarlinpe>`_, and
`Shaohui Liu <https://github.com/B1ueber2y>`_.
The Python bindings in PyCOLMAP were originally added by
`Mihai Dusmanu <https://github.com/mihaidusmanu>`_,
`Philipp Lindenberger <https://github.com/Phil26AT>`_, and
`Paul-Edouard Sarlin <https://github.com/sarlinpe>`_.
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 <https://tsattler.github.io>`_).
.. toctree::
:hidden:
:maxdepth: 2
install
tutorial
concepts
features
database
cameras
rigs
format
datasets
gui
cli
pycolmap/index
faq
changelog
contribution
license
bibliography
legacy
|
