VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss

Honda, ShionFusiello, Andrea and Bimber, Oliver2019-05-052019-05-0520191017-4656https://doi.org/10.2312/egp.20191043https://diglib.eg.org:443/handle/10.2312/egp20191043Generating a virtual try-on image from in-shop clothing images and a model person's snapshot is a challenging task because the human body and clothes have high flexibility in their shapes. In this paper, we develop a Virtual Try-on Generative Adversarial Network (VITON-GAN), that generates virtual try-on images using images of in-shop clothing and a model person. This method enhances the quality of the generated image when occlusion is present in a model person's image (e.g., arms crossed in front of the clothes) by adding an adversarial mechanism in the training pipeline.Computing methodologiesImage representationsApplied computingOnline shoppingVITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss10.2312/egp.201910439-10