用AI自动生成适配不同场合风格的个性化穿搭数据集
Prompt2Fashion: An automatically generated fashion dataset
- 通过大模型和提示词策略生成定制化穿搭图像
- 支持多种场合、风格与体型，满足专业与普通用户需求
- 强调专家评估对艺术类AI数据集的重要性
尽管语言与视觉生成模型快速演进且效果日益提升，但缺乏能连接个性化时尚需求与人工智能设计的综合性数据集，限制了真正包容性与定制化时尚解决方案的发展。本文利用生成模型，自动构建一个可根据用户指令适配不同场合、风格和体型的时尚图像数据集。通过使用不同的大型语言模型（LLMs）和提示策略，生成具有高审美质量、细节丰富且与用户需求高度相关的内容，经定性分析验证其有效性。此前生成服装的评估主要依赖非专家人类参与者，虽提供了关于生成质量与相关性的细粒度见解，但本研究进一步强调了在评估此类艺术性AI生成数据集时，专家知识的重要作用。数据集已公开于GitHub：https://github.com/georgiarg/Prompt2Fashion。
原文摘要 · Abstract (English)
Despite the rapid evolution and increasing efficacy of language and vision generative models, there remains a lack of comprehensive datasets that bridge the gap between personalized fashion needs and AI-driven design, limiting the potential for truly inclusive and customized fashion solutions. In this work, we leverage generative models to automatically construct a fashion image dataset tailored to various occasions, styles, and body types as instructed by users. We use different Large Language Models (LLMs) and prompting strategies to offer personalized outfits of high aesthetic quality, detail, and relevance to both expert and non-expert users' requirements, as demonstrated by qualitative analysis. Up until now the evaluation of the generated outfits has been conducted by non-expert human subjects. Despite the provided fine-grained insights on the quality and relevance of generation, we extend the discussion on the importance of expert knowledge for the evaluation of artistic AI-generated datasets such as this one. Our dataset is publicly available on GitHub at https://github.com/georgiarg/Prompt2Fashion.
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