让新手通过可视化维度快速生成更专业的图文设计提示。
DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design
- 从生成图像中提取产品设计关键维度，形成可选配的提示词面板。
- 52名新手使用后提示词更长、词汇更专业，设计更多样创新。
- 适合缺乏设计经验但想高效探索产品原型的新手或团队。
生成式AI使新手设计师能快速创建专业级的产品视觉图。然而，新手因领域知识有限，难以写出有效探索设计空间的提示词。我们对12位资深产品设计师进行前期研究，发现专家及其客户常借助视觉参考而非文字描述来引导共同设计讨论。这一发现催生了DesignWeaver——一个将生成图像中的关键产品设计维度提取为可选提示词面板的界面。在52名新手参与的实验中，DesignWeaver帮助用户构建更长、包含更多领域特定词汇的提示词，从而生成更具多样性与创新性的产品设计。但更精细的提示也提升了用户期望，超出当前文本到图像模型的实际表现能力。论文讨论了基于AI的设计支持工具的未来方向。
原文摘要 · Abstract (English)
Generative AI has enabled novice designers to quickly create professional-looking visual representations for product concepts. However, novices have limited domain knowledge that could constrain their ability to write prompts that effectively explore a product design space. To understand how experts explore and communicate about design spaces, we conducted a formative study with 12 experienced product designers and found that experts -- and their less-versed clients -- often use visual references to guide co-design discussions rather than written descriptions. These insights inspired DesignWeaver, an interface that helps novices generate prompts for a text-to-image model by surfacing key product design dimensions from generated images into a palette for quick selection. In a study with 52 novices, DesignWeaver enabled participants to craft longer prompts with more domain-specific vocabularies, resulting in more diverse, innovative product designs. However, the nuanced prompts heightened participants' expectations beyond what current text-to-image models could deliver. We discuss implications for AI-based product design support tools.
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