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Generating video game characters using StyleGAN2

Year 2023, Volume: 8 Issue: 1, 57 - 61, 03.02.2023

Abstract

GANs have been getting better and better each year. The state of the art GAN models for generating 2D images have become so good it is hard to differentiate generated images nowadays. In this paper we create 3 different sparse data sets from video game assets and train them with StyleGAN2 to generate new artwork based on the previously existing artworks of the video game in question

References

  • BRADISKI, G. (2000). The OpenCV Library. Dr. Dobb’s Journal of Software Tools, 2000.
  • Karras et al. Analyzing and improving the image quality of StyleGAN.
  • Karras et al. A style-based generator architecture for generative adversarial networks.
  • Karras et al. Training generative adversarial networks with limited data.
  • The ImageMagick Development Team. Imagemagick.
Year 2023, Volume: 8 Issue: 1, 57 - 61, 03.02.2023

Abstract

References

  • BRADISKI, G. (2000). The OpenCV Library. Dr. Dobb’s Journal of Software Tools, 2000.
  • Karras et al. Analyzing and improving the image quality of StyleGAN.
  • Karras et al. A style-based generator architecture for generative adversarial networks.
  • Karras et al. Training generative adversarial networks with limited data.
  • The ImageMagick Development Team. Imagemagick.
There are 5 citations in total.

Details

Primary Language English
Journal Section Research Article
Authors

İsmail Ergen This is me 0000-0002-8847-7262

Publication Date February 3, 2023
Published in Issue Year 2023 Volume: 8 Issue: 1

Cite

APA Ergen, İ. (2023). Generating video game characters using StyleGAN2. Journal of Awareness, 8(1), 57-61.