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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

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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

About

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

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