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Revisiting Sliced Wasserstein on Images: From Vectorization to Convolution. (arXiv:2204.01188v4 [cs.CV] UPDATED)
Sept. 26, 2022, 1:12 a.m. | Khai Nguyen, Nhat Ho
stat.ML updates on arXiv.org arxiv.org
The conventional sliced Wasserstein is defined between two probability
measures that have realizations as vectors. When comparing two probability
measures over images, practitioners first need to vectorize images and then
project them to one-dimensional space by using matrix multiplication between
the sample matrix and the projection matrix. After that, the sliced Wasserstein
is evaluated by averaging the two corresponding one-dimensional projected
probability measures. However, this approach has two limitations. The first
limitation is that the spatial structure of images is …
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