DesignWeaver: Dimensional Scaffolding for Text-to-Image Product Design
Sirui Tao, Ivan Liang, Cindy Peng, Zhiqing Wang, Srishti Palani, Steven P. Dow

TL;DR
DesignWeaver is a tool that helps novice designers craft better prompts for text-to-image AI models by highlighting key design dimensions, leading to more diverse and innovative product concepts.
Contribution
The paper introduces DesignWeaver, an interface that surfaces design dimensions to assist novices in generating more effective prompts for AI-driven product design.
Findings
Novices using DesignWeaver created more diverse designs.
DesignWeaver enabled longer, more domain-specific prompts.
Participants' expectations exceeded current AI capabilities.
Abstract
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…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
