Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2025

Abstract

With the increasing demand for outfit planning in real-world travel scenarios, the need for constructing a travel fashion wardrobe, a series of outfits tailored to a user's personalization and destination-specific context over a short travel period, has grown significantly. However, existing systems or works often focus on isolated factors and rely on retrieval-based methods, with insufficient utilization of generative models, limiting their adaptability to real-world travel scenarios. To address this issue, this study introduces GenWardrobe, a fully generative system for travel fashion wardrobe construction. GenWardrobe consists of three key modules: user query analysis, fashion knowledge retrieval via retrieval-augmented generation and wardrobe image generation. To facilitate users' usage, we encapsulate the solution into an interactive web application. Expert-level evaluation shows that GenWardrobe significantly outperforms traditional systems in both personalization and visual appeal. PowerPoint file and more materials of Genwordrobe can be found on our Github repository: https://github.com/ShanFengShanFeng/GenWardrobe.

Keywords

Fashion Wardrobe Construction, Image Generation, Multimodality

Discipline

Artificial Intelligence and Robotics | Graphics and Human Computer Interfaces

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

MM '25: Proceedings of the 33rd ACM International Conference on Multimedia, Dublin, Ireland, October 27-31

First Page

13540

Last Page

13542

Identifier

10.1145/3746027.3754483

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3746027.3754483

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