The logo of Amazon is seen at the company logistics center in Boves, France, September 18, 2019. Image Credit: Reuters / Pascal Rossignol

Generative adversarial networks (GANs) — two-part AI models consisting of a generator that creates samples and a discriminator that attempts to differentiate between the generated samples and real-world samples — have been applied to tasks ranging from video, artwork, and music synthesis to drug discovery and misleading media detection. They’ve also made their way into ecommerce, as Amazon revealed in a blog post this morning. Scientists at Amazon describe a GAN that generates clothing examples to match product descriptions, which they say could be used to refine customer text queries. For instance, if a shopper searched for “women’s black pants” and then add the word “petite” and then the word “capri,” the on-screen images would adjust accordingly with each new word.

It’s not unlike the GAN model commercialized by startup Vue.ai, which susses out clothing characteristics and learns to produce realistic poses, skin colors, and other features. From snapshots of apparel, it’s able to generate model images in every size up to 5 times faster than a traditional photoshoot.

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Originally posted by:

Kyle Wiggers

www.venturebeat.com

March 2nd, 2020