# VTON-IT: Virtual Try-On using Image Translation

**Authors:** Santosh Adhikari, Bishnu Bhusal, Prashant Ghimire, Anil Shrestha  
**arXiv:** [2310.04558](https://arxiv.org/abs/2310.04558)  
**Date:** 2023-10-06  
**Summary page:** https://www.summarizepaper.com/fr/paper/2310.04558v2/

## Abstract

Virtual Try-On (trying clothes virtually) is a promising application of the Generative Adversarial Network (GAN). However, it is an arduous task to transfer the desired clothing item onto the corresponding regions of a human body because of varying body size, pose, and occlusions like hair and overlapped clothes. In this paper, we try to produce photo-realistic translated images through semantic segmentation and a generative adversarial architecture-based image translation network. We present a novel image-based Virtual Try-On application VTON-IT that takes an RGB image, segments desired body part, and overlays target cloth over the segmented body region. Most state-of-the-art GAN-based Virtual Try-On applications produce unaligned pixelated synthesis images on real-life test images. However, our approach generates high-resolution natural images with detailed textures on such variant images.