SakugaFlow模拟人类绘画步骤，支持新手边画边学。
SakugaFlow: A Stagewise Illustration Framework Emulating the Human Drawing Process and Providing Interactive Tutoring for Novice Drawing Skills
- 分四阶段生成，每步可非线性修改
- 实时反馈解剖、透视、构图问题
- 适合绘画初学者和交互式教学场景
当前AI绘图工具虽能根据文本生成高质量图像，却极少展现人类艺术家的逐步创作过程。我们提出SakugaFlow，一个四阶段流程，将基于扩散模型的图像生成与大型语言模型导师结合。每个阶段中，新手可获得解剖、透视、构图方面的实时反馈，支持非线性修正和分支生成不同版本。通过暴露中间输出并嵌入教学对话，SakugaFlow将黑箱生成器转化为支持创意探索与技能习得的阶梯式学习环境。
原文摘要 · Abstract (English)
While current AI illustration tools can generate high-quality images from text prompts, they rarely reveal the step-by-step procedure that human artists follow. We present SakugaFlow, a four-stage pipeline that pairs diffusion-based image generation with a large-language-model tutor. At each stage, novices receive real-time feedback on anatomy, perspective, and composition, revise any step non-linearly, and branch alternative versions. By exposing intermediate outputs and embedding pedagogical dialogue, SakugaFlow turns a black-box generator into a scaffolded learning environment that supports both creative exploration and skills acquisition.
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