GarmentGAN: Photo-realistic Adversarial Fashion Transfer

Understand

The garment transfer problem comprises two tasks: learning to separate a person's body (pose, shape, color) from their clothing (garment type, shape, style) and then generating new images of the wearer dressed in arbitrary garments.

• We present GarmentGAN, a new algorithm that performs image-based garment transfer through generative adversarial methods.
• The GarmentGAN framework allows users to virtually try-on items before purchase and generalizes to various apparel types.
• GarmentGAN requires as input only two images, namely, a picture of the target fashion item and an image containing the customer.