At Amazon Lab126, researchers proposed three related AI algorithms to create Outfit-VITON, an image-based virtual try-on system for apparel. The algorithms could form the basis of an assistant to help a customer shop for clothes by describing a product’s variations, recommending items that go with the one selected, and synthesizing the image of a model wearing clothes to show how all the items work as an outfit. The algorithms will be presented at the annual IEEE Conference on Computer Vision and Pattern Recognition (CVPR will be held virtually this year, June 14-19). Continue reading Amazon Developing AI System for Trying on Clothes Virtually

Amazon, which launched its new StyleSnap feature to select iOS and Android users in April, will soon make the in-app tool widely available, said company worldwide consumer head Jeff Wilke at the company’s re:MARS AI conference in Las Vegas. Users can reach StyleSnap via a shortcut found by tapping the camera icon in the Amazon app’s upper right-hand corner. Based on image recognition, the machine learning-enabled StyleSnap (and Pinterest Lens competitor) will offer similar items to any photo or screenshot uploaded by a user. The algorithms also incorporate computer vision and deep learning. Continue reading Amazon’s AI-Enabled StyleSnap Is Ideal for Fashion Market

Amazon is developing systems based on artificial intelligence algorithms that are aimed at spotting fashion trends and, eventually, shaping them. The effort could boost Amazon’s sales in clothing, perhaps even gaining a dominant position in fashion. The e-commerce giant isn’t alone in making recommendations based on products appearing in social media, and highlighting the resulting trends; Instagram and Pinterest also pinpoint trends and react quickly to them, as does startup subscription service Stitch Fix. Continue reading Amazon Creates AI-Based Tools for Spotting Fashion Trends