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

Shion Honda

doi:10.2312/egp.20191043

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arXiv · 1911.07926

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

Shion Honda

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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.

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BibTeX RIS

Shion Honda. 2019-11-12. VITON-GAN: Virtual Try-on Image Generator Trained with Adversarial Loss. https://doi.org/10.2312/egp.20191043

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