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

• URL: http://arxiv.org/abs/2508.09207v1
• Date: Sun, 10 Aug 2025 02:20:19 GMT
• Title: GANime: Generating Anime and Manga Character Drawings from Sketches with Deep Learning
• Authors: Tai Vu, Robert Yang,
• Abstract summary: We examine three models for image-to-image translation between anime characters and their sketches, including Neural Style Transfer, C-GAN, and CycleGAN.<n>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.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• 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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