Garment Style Creator: Using StarGAN for Image-to-Image Translation of Multidomain Garments

On the basis of StarGAN, this study developed a garment style-generation system named Garment Style Creator. This system first requires the user to import a human image to produce distinct parts, such as head, arms, and garment by applying the human parsing technique. Then, this system separates the training images that contain only the garment part and removes the other semantic parts as background. Subsequently, images of the garment are imported into StarGAN to produce images of multiple garment styles and concurrently generate garment images of the human model wearing plain, lattice, stripe, and polka-dotted fabrics. Finally, we designed a style-mixing system that allows users to blend multiple garment images into one image. The system facilitates the generation of images of numerous garment styles simultaneously and thus assists designers and users in finding the ideal garment style for them.