AI 中文总结
EasyFashion是一个利用参考图像、文本和身体照片输入，通过虚拟试穿和缝纫图案生成，实现个性化服装设计的人机协同创作系统，经实验验证其有效支持多模态表达与生产导向输出。
AI 中文摘要
人们通常希望拥有能反映其审美偏好、贴合其体型并满足其尺码需求的服装，然而将这些需求转化为实体服装仍然困难重重。成衣选项提供的个性化程度有限，而定制裁剪则成本高昂且耗时。近期的生成式人工智能（AI）系统能够可视化服装创意，但往往止步于支持下游生产。为弥补这一缺口，我们提出了EasyFashion，一个人机协同创作系统，使用户能够迭代地细化针对个性化服装款式和尺码的设计意图，在重建的个人虚拟形象上通过虚拟试穿评估设计，并生成用于服装生产的缝纫图案。以参考图像、文本描述和身体照片为输入，EasyFashion将用户意图转化为结构化的服装规格和试穿结果。技术实验、用户研究以及一个真实世界的生产案例证明了EasyFashion在个性化服装设计中对于多模态设计表达、基于身体特征的评估以及面向生产的输出的价值。
英文摘要
People often want garments that reflect their aesthetic preferences, fit their bodies, and meet their sizing needs, yet turning these requirements into physical garments remains difficult. Ready-to-wear options provide limited personalization, while custom tailoring is costly and time-consuming. Recent generative artificial intelligence (AI) systems can visualize garment ideas but often stop short of supporting downstream production. To address this gap, we present EasyFashion, a human-AI co-creation system that enables users to iteratively refine design intent for personalized garment style and size, evaluate designs through virtual try-on on reconstructed personal avatars, and generate sewing patterns for garment production. Using reference images, text descriptions, and body photos as input, EasyFashion translates user intent into structured garment specifications and try-on results. Technical experiments, user studies, and a real-world production case demonstrate the value of EasyFashion for multimodal design expression, body-specific evaluation, and production-oriented outputs in personalized garment design.
Comments29 pages, 15 figures
