Generating and Modifying High Resolution Fashion Model Image using StyleGAN

Abstract

In this paper, a research of synthesizing fashion model images by utilizing a state-of-the-art generative adversarial network (i.e., GAN) is introduced. After training GAN with fashion model images, the network was able to generate realistic fashion model images having various characteristics such as pose and clothes. Moreover, two image modifications named Fashion Model Morphing and Fashion Transfer are also proposed by merging attributes of two generated fashion model images. The research investigates the effectiveness of using GAN for fashion to create a large number of images for exploring new design and styles. The generated images are even more beneficial for fashion industries because the generated images have no legal issues such as portrait right and copyright.