Effective collaboration between designers and users is important for fashion design, which can increase the user acceptance of fashion products and thereby create value. However, it remains an enduring challenge, as traditional designer-centric approaches restrict meaningful user participation, while user-driven methods demand design proficiency, often marginalizing professional creative judgment. Current co-design practices, including workshops and AI-assisted frameworks, struggle with low user engagement, inefficient preference collection, and difficulties in balancing user feedback with design considerations. To address these challenges, we conducted a formative study with designers and users experienced in co-design (N=7), identifying critical challenges for current collaboration between designers and users in the co-design process, and their requirements. Informed by these insights, we introduce DesignBridge, a multi-platform AI-enhanced interactive system that bridges designer expertise and user preferences through three stages: (1) Initial Design Framing, where designers define initial concepts. (2) Preference Expression Collection, where users intuitively articulate preferences via interactive tools. (3) Preference-Integrated Design, where designers use AI-assisted analytics to integrate feedback into cohesive designs. A user study demonstrates that DesignBridge significantly enhances user preference collection and analysis, enabling designers to integrate diverse preferences with professional expertise.

翻译：设计师与用户之间的有效协作对于时尚设计至关重要，它能提升时尚产品的用户接受度从而创造价值。然而，这始终是一项持久的挑战：传统以设计师为中心的方法限制了用户的有效参与，而用户驱动的方法则要求设计专业能力，往往使专业创意判断被边缘化。当前的协同设计实践（包括工作坊和AI辅助框架）面临用户参与度低、偏好收集效率不足以及用户反馈与设计考量难以平衡等问题。为应对这些挑战，我们与具有协同设计经验的设计师和用户（N=7）开展了一项形成性研究，识别出当前协同设计过程中设计师与用户协作的关键难点及其需求。基于这些发现，我们提出了DesignBridge——一个多平台AI增强交互系统，通过三个阶段连接设计师专业能力与用户偏好：（1）初始设计框架构建阶段，设计师定义初始概念；（2）偏好表达收集阶段，用户通过交互工具直观阐述偏好；（3）偏好整合设计阶段，设计师运用AI辅助分析将反馈整合为协调的设计方案。用户研究表明，DesignBridge显著提升了用户偏好收集与分析效率，使设计师能够将多元偏好与专业能力有效融合。