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- W3207830738 abstract "This paper presents an application of the Generative Adversarial Networks (GAN) approach to automatically generate realistic-looking fantasy and science fiction game icons. In this study, we explored ways to avoid the manual drawing of graphics, instead producing synthetic images indistinguishable from artist-made ones. We developed the method based on multiple experiments and commonly known GAN improvement techniques." @default.
- W3207830738 created "2021-10-25" @default.
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- W3207830738 date "2021-07-13" @default.
- W3207830738 modified "2023-09-30" @default.
- W3207830738 title "Automatic generation of graphical game assets using GAN" @default.
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- W3207830738 doi "https://doi.org/10.1145/3477911.3477913" @default.
- W3207830738 hasPublicationYear "2021" @default.
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