Photo Credit: Daily Mail
Researchers at the University of California, San Diego, and Adobe have recently created a way for AI to both learn a person’s style and create images of items that match the style. The system could potentially allow retailers to create personalized clothing, or help predict fashion trends.
The two algorithms used are a convolutional neural network (CNN) and a generative adversarial network (GAN). The two networks improve the results and can create multiple item images for each user. There’s still a few obstacles to these AI-generated textiles hitting the market, however. For example, researchers need to turn two-dimensional computer images into 3-D images used to produce an actual piece of clothing. And of course, fashion sense requires knowing which items pair well together.
Amazon has been working on using AI to spot fashion trends, and Alibaba, a Chinese retail giant, has introduced FashionAI, which recommends items based on what shoppers brought into the dressing room.
Vue.ai is a fashion AI startup that recently revealed a method for creating fake fashion models. Last fall, Burberry launched a Facebook Messenger bot during London Fashion Week, which offered glimpses of the new collection and shared trivia, as well as a live buying option. HighSnobiety is a website covering streetwear trends, which also launched a Sneaker Bot on Facebook Messenger, which quickly conveyed information and news from different brands.
This is just the tip of the iceberg when it comes to AI applications in fashion. It’s an exciting field, with many high-profile clients and players.
MIT Tech Review