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AI Assisted Fashion Design: A Review

2023; Institute of Electrical and Electronics Engineers; Volume: 11; Linguagem: Inglês

10.1109/access.2023.3306235

2169-3536

Ziyue Guo, Zongyang Zhu, Yi‐Zhi Li, Shidong Cao, Hangyue Chen, Gaoang Wang,

Color perception and design

This review explores the integration of enhanced personalization and seamless multimodal interfaces in the field of fashion design and recommendation. We examine the increasing demand for personalized fashion experiences and the potential of multimodal interfaces in facilitating effective communication between designers and users. By leveraging user preferences, body measurements, and style choices, artificial intelligence (AI) systems can deliver highly personalized fashion recommendations. The integration of various input modalities, including text, images and sketches, enables designers and users to communicate their design ideas with ease. The primary results highlight the transformative potential of enhanced personalization and seamless multimodal interfaces, empowering designers and consumers to co-create unique and personalized designs. This paradigm shift fosters a deeper level of engagement and creativity within the fashion industry. Embracing this advancement unlocks unprecedented opportunities for designers, brands, and consumers, ushering in a new era of innovation and creativity in fashion design.