Unsupervised Image-to-Video Clothing Transfer

We present a system to photo-realistically transfer the clothing of a person in a reference image into another person in an unconstrained image or video. Our architecture is based on a GAN equipped with a physical memory that updates an initially incomplete texture map of the clothes that is progressively completed with the new inferred occluded parts. The system is trained in an unsupervised manner. The results are visually appealing and open the possibility to be used in the future as a quick virtual try-on clothing system.