GANime: Generating Anime and Manga Character Drawings from Sketches with Deep Learning

Tai Vu, Robert Yang
8/10/2025
cs.CVcs.LG

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Abstract

The process of generating fully colorized drawings from sketches is a large, usually costly bottleneck in the manga and anime industry. In this study, we examine multiple models for image-to-image translation between anime characters and their sketches, including Neural Style Transfer, C-GAN, and CycleGAN. By assessing them qualitatively and quantitatively, we find that C-GAN is the most effective model that is able to produce high-quality and high-resolution images close to those created by humans.

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Cite this paper

@article{vu2025ganime,
  title  = {GANime: Generating Anime and Manga Character Drawings from Sketches with Deep Learning},
  author = {Tai Vu and Robert Yang},
  year   = {2025},
  eprint = {2508.09207},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2508.09207v1}
}

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