🤖 AI Summary
This work addresses the creative stagnation often induced by existing generative design tools that directly output complete images. To overcome this limitation, the authors propose a multi-stage, compositional AI-assisted design approach that emulates professional designers’ workflows: it first structurally interprets ambiguous design requests, then generates candidate elements—such as objects, backgrounds, typography, layout, and composition—separately, and finally enables interactive recombination. This method formalizes real-world design processes into a computable system for the first time, decoupling requirement interpretation, element generation, and composition to substantially enhance prompt diversity and alignment with user intent. User studies demonstrate that the system outperforms baseline approaches in both requirement comprehension accuracy and designer-rated quality, revealing a productive trade-off between structured workflow, creative clarity, and efficiency despite slightly longer generation times.
📝 Abstract
Professional designers work from client briefs that specify goals and constraints but often lack concrete design details. Translating these abstract requirements into visual designs poses a central challenge, yet existing tools address specific aspects or induce fixation through complete outputs. Through interviews with six professional designers, we identified how designers address this challenge: first structuring ambiguous requirements, then exploring individual elements, and finally recombining alternatives. We developed Brief2Design, supporting this workflow through requirement extraction and recommendation, element-level exploration for objects, backgrounds, text, typography, and composition, and flexible recombination of selected elements. A within-subjects study with twelve designers compared Brief2Design against a conversational baseline. The structured approach increased prompt diversity and received high ratings for requirement extraction and recommendation, but required longer generation time and achieved comparable image diversity. These findings reveal that structured workflows benefit requirement clarification at the cost of efficiency, informing design trade-offs for AI-assisted graphic design tools.