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arXiv · 2002.07897

LocoGAN -- Locally Convolutional GAN

Łukasz Struski·Szymon Knop·Jacek Tabor·Wiktor Daniec·Przemysław Spurek
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Abstract

In the paper we construct a fully convolutional GAN model: LocoGAN, which latent space is given by noise-like images of possibly different resolutions. The learning is local, i.e. we process not the whole noise-like image, but the sub-images of a fixed size. As a consequence LocoGAN can produce images of arbitrary dimensions e.g. LSUN bedroom data set. Another advantage of our approach comes from the fact that we use the position channels, which allows the generation of fully periodic (e.g. cylindrical panoramic images) or almost periodic ,,infinitely long" images (e.g. wall-papers).

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Łukasz Struski, Szymon Knop, Jacek Tabor, Wiktor Daniec, Przemysław Spurek. 2020-02-18. LocoGAN -- Locally Convolutional GAN. https://arxiv.org/abs/2002.07897

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