Google’s generative AI is improving virtual fitting rooms

Today we announced virtual try-on for apparel, a new feature that shows you what clothes look like on real models with different body shapes and sizes. That includes those subtle but crucial details, like how something drapes, folds, clings, stretches and wrinkles. To do this, our shopping AI researchers developed a new generative AI model that produces life-like portrayals of clothing on people.

Let’s take a closer look at this new AI model and how exactly it powers our virtual try-on (VTO) feature.

Generating try-on images with AI

Perhaps the most popular reference for VTO dates back to the movie “Clueless.” We’ve come a long way since Cher’s closet, though. Current techniques like geometric warping can cut-and-paste and then deform a clothing image to fit a silhouette. Even so, the final images never quite hit the mark: Clothes don’t realistically adapt to the body, and they have visual defects like misplaced folds that make garments look misshapen and unnatural.

So when we set out to build a new VTO feature, we were committed to generating every pixel of a garment from scratch to produce high-quality, realistic images. We found a way with our new diffusion-based AI model.

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