English

Interactive Drawing Guidance for Anime Illustrations with Diffusion Model

Graphics 2025-07-15 v1

Abstract

Creating high-quality anime illustrations presents notable challenges, particularly for beginners, due to the intricate styles and fine details inherent in anime art. We present an interactive drawing guidance system specifically designed for anime illustrations to address this issue. It offers real-time guidance to help users refine their work and streamline the creative process. Our system is built upon the StreamDiffusion pipeline to deliver real-time drawing assistance. We fine-tune Stable Diffusion with LoRA to synthesize anime style RGB images from user-provided hand-drawn sketches and prompts. Leveraging the Informative Drawings model, we transform these RGB images into rough sketches, which are further refined into structured guidance sketches using a custom-designed optimizer. The proposed system offers precise, real-time guidance aligned with the creative intent of the user, significantly enhancing both the efficiency and accuracy of the drawing process. To assess the effectiveness of our approach, we conducted a user study, gathering empirical feedback on both system performance and interface usability.

Keywords

Cite

@article{arxiv.2507.09140,
  title  = {Interactive Drawing Guidance for Anime Illustrations with Diffusion Model},
  author = {Chuang Chen and Xiaoxuan Xie and Yongming Zhang and Tianyu Zhang and Haoran Xie},
  journal= {arXiv preprint arXiv:2507.09140},
  year   = {2025}
}

Comments

9 pages, 7 figures. In proceedings of NICOGRAPH International 2025

R2 v1 2026-07-01T03:57:39.722Z