Human-Centric GenAI Garment Designer: 3D Fashion Design Recommendations
This study proposes a 3D fashion design recommendation system that integrates Generative AI (GenAI) and consumer electronics technology to enhance the online shopping experience. Users can upload full-body images to the platform, where GenAI analyzes their body shape and suggests suitable outfit options. This system addresses a significant issue in the consumer electronics industry: the frequent occurrence of mismatched clothing purchases in online shopping, which often leads to high return rates and customer dissatisfaction. By providing personalized and accurate fashion recommendations, our system aims to bridge the gap between online and physical shopping experiences. The method utilizes GenAI to recognize and interpret body shapes, ensuring that the recommended outfits match the user's physique. Experimental results demonstrate the effectiveness of the proposed system in accurately identifying body shapes and offering tailored fashion advice. This innovation not only improves user satisfaction by reducing the likelihood of returns but also contributes to resource conservation by minimizing the amount of unused clothing.
Authors
- Sherali Zeadally (ORCID: https://orcid.org/0000-0002-5982-8190)
- Hsin‐Hung Cho (ORCID: https://orcid.org/0000-0001-7163-6928)
- Wei-Che Chien (ORCID: https://orcid.org/0000-0002-0172-9958)
Institutions
- University of Kentucky (US)
- National Dong Hwa University (TW)
- National Ilan University (TW)
Publication Details
- Journal
- IEEE Consumer Electronics Magazine
- Published
- 2024-11-06
- DOI
- https://doi.org/10.1109/mce.2024.3492510
- Primary Topic
- Fashion and Cultural Textiles
- Type
- article
- Field-Weighted Citation Impact
- 0.00