Scientists have developed a system that can design new clothes based on people’s personal taste using artificial intelligence (AI).
Online retailers are already using AI to recommend products to buyers, but researchers wanted to take it a step further by creating an algorithm to “produce new clothing designs”.
The project is an attempt to test whether machine learning can help the fashion industry as well as consumers, particularly online shoppers.
The team trained an algorithm known as the Siamese convolutional neural network (Siamese-CNN) to learn and classify a user’s preference for certain items.
Using Siamese-CNNs as the base, the researchers then developed another neural network called a generative adversarial network (GAN) to generate realistic images of “novel fashion items that maximise users’ preferences”.
The researchers say their system can suggest items to buy from existing designs, modify existing designs and generate new designs tailored to a specific individual’s preferences.
Study leader Wang-Cheng Kang, from the University of California, San Diego, said: “Building effective recommender systems for domains like fashion is challenging due to the high level of subjectivity and the semantic complexity of the features involved.
“This represents a first step towards building systems that go beyond recommending existing items from a product corpus, to suggesting styles and helping to design new products.”
E-commerce giants Amazon and Alibaba are said to be working on GANs and other AI tools, although the researchers say the use of AI in the fashion industry is still in its infancy.
The findings are published on ArXiv.
