纺织学报 ›› 2021, Vol. 42 ›› Issue (07): 164-168.doi: 10.13475/j.fzxb.20200803505

• 服装工程 • 上一篇    下一篇


杨争妍1, 薛文良1(), 张传雄2, 丁亦1, 马颜雪1   

  1. 1.东华大学 纺织学院, 上海 201620
    2.纺织工业科学技术发展中心, 北京 100020
  • 收稿日期:2020-08-05 修回日期:2021-04-22 出版日期:2021-07-15 发布日期:2021-07-22
  • 通讯作者: 薛文良
  • 作者简介:杨争妍(1998—),女,硕士生。主要研究方向为人工智能在纺织品设计中的应用。

Recommendations for user's bottoms matching based on generative adversarial networks

YANG Zhengyan1, XUE Wenliang1(), ZHANG Chuanxiong2, DING Yi1, MA Yanxue1   

  1. 1. College of Textiles, Donghua University, Shanghai 201620, China
    2. Science and Technology Development Center of Textile Industry, Beijing 100020, China
  • Received:2020-08-05 Revised:2021-04-22 Published:2021-07-15 Online:2021-07-22
  • Contact: XUE Wenliang



关键词: 深度学习, 生成式对抗网络, 智能穿搭, 服装搭配


In order to avoid repetitive purchases of similar clothes and to solve the clothing matching problem, this research worked on an intelligent clothing matching system for providing recommendations to customers and end-users. A crawler technology was used to obtain a large number of clothing matching data from mid-to-high end brands, and the model of deep learning-generative adversarial network (GAN) was adopted to learn clothing data to explore the visual perceptions of colors, styles, and so on. When inputting a piece of top clothing in the system, a bottom picture can be generated intelligently and then matched to the user's personal wardrobe together with the consideration of the surrounding temperature. The effectiveness of this method was verified by comparing the original matching with the model generated matching.This work provides new ideas for intelligent clothing matching.

Key words: deep learning, generative adversarial networks, intelligent decision on clothing match, clothing match


  • TS941.13











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