用自然语言生成SVG动画，让设计无需代码即可快速试错。
Decomate: Leveraging Generative Models for Co-Creative SVG Animation
- 用大语言模型解析SVG，自动拆分出可动的语义组件。
- 用户写文字指令控制每个组件运动，系统自动生成HTML/CSS/JS代码。
- 适合想快速原型但不懂编程的设计师，支持语言反复修改。
设计师在为静态SVG图形添加动画时常遇障碍，尤其当视觉结构与期望的动态细节不匹配时。现有工具多依赖预定义分组或需技术知识，限制了独立实验和迭代的能力。我们提出Decomate，一个通过自然语言实现直观SVG动画的系统。Decomate利用多模态大语言模型将原始SVG重构为具有语义意义、可直接用于动画的组件。设计师随后可通过文本提示指定各组件的运动，系统则生成对应的HTML/CSS/JS动画代码。通过支持自然语言交互下的迭代优化，Decomate将生成式AI融入创作流程，使动画结果直接由用户意图驱动。
原文摘要 · Abstract (English)
Designers often encounter friction when animating static SVG graphics, especially when the visual structure does not match the desired level of motion detail. Existing tools typically depend on predefined groupings or require technical expertise, which limits designers' ability to experiment and iterate independently. We present Decomate, a system that enables intuitive SVG animation through natural language. Decomate leverages a multimodal large language model to restructure raw SVGs into semantically meaningful, animation-ready components. Designers can then specify motions for each component via text prompts, after which the system generates corresponding HTML/CSS/JS animations. By supporting iterative refinement through natural language interaction, Decomate integrates generative AI into creative workflows, allowing animation outcomes to be directly shaped by user intent.
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