Work

Sketch-Guided Anime Hair Editing Using Multimodal Diffusion Transformer (Student Abstract)

Year: 2026

Type: other

Abstract: Anime hair design is crucial but challenging, as it conveys personality and emotion through stylized geometry and layered structure. In this work, we propose a sketch-guided approach for intuitive control of multimodal diffusion transformers (MMDiT) to generate semantically consistent anime hairstyles. We adopt a wisp-level flowline input integrated with a fine-tuned MMDiT to transfer hairstyles while preserving character identity. We believe that this fine-grained sketch control within the MMDiT framework may offer a promising path for structured anime hair editing.

Source: Underline Science Inc.

DOI: 10.48448/xr5h-rp30

Authors: Association for Artificial Intelligence 2026, Shen, I-Chao, Xie, Haoran, Zhang, Tianyu

Language: English

Topic: Generative Adversarial Networks and Image Synthesis

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7128726727

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