VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss
dc.contributor.author | Honda, Shion | en_US |
dc.contributor.editor | Fusiello, Andrea and Bimber, Oliver | en_US |
dc.date.accessioned | 2019-05-05T17:47:59Z | |
dc.date.available | 2019-05-05T17:47:59Z | |
dc.date.issued | 2019 | |
dc.description.abstract | Generating 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. | en_US |
dc.description.sectionheaders | Posters | |
dc.description.seriesinformation | Eurographics 2019 - Posters | |
dc.identifier.doi | 10.2312/egp.20191043 | |
dc.identifier.issn | 1017-4656 | |
dc.identifier.pages | 9-10 | |
dc.identifier.uri | https://doi.org/10.2312/egp.20191043 | |
dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/egp20191043 | |
dc.publisher | The Eurographics Association | en_US |
dc.subject | Computing methodologies | |
dc.subject | Image representations | |
dc.subject | Applied computing | |
dc.subject | Online shopping | |
dc.title | VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss | en_US |