FIT-ME: IMAGE-BASED VIRTUAL TRY-ON WITH ARBITRARY POSES

Abstract

The image-based virtual try-on system has raised research attention recently, but it still requires to upload an image of a user with the target pose. We present a novel learning model, Fit-Me network, to seamlessly fit in-shop clothing into a person image and simultaneously transform the pose of the person image to another given one. The proposed Fit-Me network helps users not only save the time used to change clothes physically but also provide comprehensive information about how suitable the clothes are. By facilitating the arbitrary pose transformation, we can generate consecutive poses to help users get more information for deciding whether to buy the clothes or not from different aspects.