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TileGAN: Synthesis of Large-Scale Non-Homogeneous Textures

2019-04-29Code Available0· sign in to hype

Anna Frühstück, Ibraheem Alhashim, Peter Wonka

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Abstract

We tackle the problem of texture synthesis in the setting where many input images are given and a large-scale output is required. We build on recent generative adversarial networks and propose two extensions in this paper. First, we propose an algorithm to combine outputs of GANs trained on a smaller resolution to produce a large-scale plausible texture map with virtually no boundary artifacts. Second, we propose a user interface to enable artistic control. Our quantitative and qualitative results showcase the generation of synthesized high-resolution maps consisting of up to hundreds of megapixels as a case in point.

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