J. Solomon, F. de Goes, G. Peyré, M. Cuturi, A. Butscher, A. Nguyen, T. Du, L. Guibas. Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains. ACM Transactions on Graphics (Proc. SIGGRAPH 2015), 34(4), pp. 66:1–66:11, 2015
Matlab TeX C++ C CMake M GLSL
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README.md

README.md

This toolbox reproduces the numerical results of the paper:

Justin Solomon, Fernando de Goes, Gabriel Peyré, Marco Cuturi, Adrian Butscher, Andy Nguyen, Tao Du, Leonidas Guibas, Convolutional Wasserstein Distances: Efficient Optimal Transportation on Geometric Domains, Proc. SIGGRAPH 2015.

Wasserstein barycenters of volumetric histograms

Content

The main directories are:

  • data/: images and meshes datasets.
  • code/: code directory, with the following sub-directories:
    • cpp/: C++ implementation of the algorithm.
    • figures/: Matlab scripts to reproduce the figure of the article.
    • tests/: Matlab scripts to reproduce some further examples not shown in the article.
    • convolutional_wasserstein/: Matlab main functions implementing the algorithms.
    • toolbox/: Matlab helper functions.
    • blur_functions/ and mesh_functions/: Matlab function to compute heat kernels.
    • colors_functions/: exernal library (c) Pascal Getreuer.
    • image_blur/: external library imgaussian (c) Dirk-Jan Kroon

Copyright

Copyright (c) 2015, Justin Solomon, Fernando de Goes, Gabriel Peyré, Marco Cuturi, Adrian Butscher, Andy Nguyen, Tao Du, Leonidas Guibas