VTON-IT: Virtual Try-On using Image Translation
Santosh Adhikari Bishnu Bhusal Prashant Ghimire Anil Shrestha
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.