The 2015-siggraph-convolutional-ot from gpeyre

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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

MATLAB 42.91% C 10.87% CMake 0.84% C++ 13.71% GLSL 0.16% M 0.55% TeX 30.97%

2015-siggraph-convolutional-ot's Introduction

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.

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