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Our initiative aims to transform the online shopping experience and the fashion business by improving virtual try-on technology. Utilizing cutting-edge technologies like Graphonomy, Generative Adversarial Networks (GANs), and the U2 Net architecture, we suggest a Virtual Try-On Network (VTON) that provides incredibly lifelike and customized virtual clothing, accessories, and cosmetics based on each user's distinct facial features and body type. The smooth overlay of virtual products over user photos, accurate body posture capture, and exact garment segmentation are all made possible by the integration of these technologies. Our approach exhibits better performance than current methods, providing improved fit accuracy, visual fidelity, and user happiness, as proven by thorough testing and review. In the constantly changing world of digital retail, our project not only solves the shortcomings of conventional try-on techniques but also creates new opportunities for tailored shopping experiences and increased sales.
Raswanth et al. (Fri,) studied this question.