Virtual Dressing Room System using Deep Neural Networks

Abstract

Abstract: In earlier twenty first century, fashion trends has evolved into a way of life. Depending on skin tone, physical stature, gender, as well as social and geographic factors, the amount and style of clothes which we worn might vary significantly. For the huge chunk of population, the in-store buying experience ( buying in the shops ) is still what comes to mind when they think of shopping. The customers can try on clothing in real time, but this process takes too long when there will not be enough trial rooms in the dressing store. The goal here is to create an engaging, interactive, involving and incredibly realistic virtual system that allow the users or customers to select from a wide variety of clothing designs before simulating those outfits on the people or customers virtually. In this study, we have proposed a system that aids in the synchronization of daily attire of the people. The Virtual styling room using live video feed may alter how a person will shop for and tries on new clothing. Customers or people can try on a wide range of clothing items without a need to actually wear them by making use of the idea of “Virtual Reality”. The benefit of doing things in this way is that it would take less time and effort of the people or customers to physically try the garments on. The project we did also aids in market management, reducing the requirement for customers to try on each and every article of clothing in clothing store. Additionally, retailers can save time, money, and space by not keeping a large inventory on hand (in store). This project aims at transferring a target clothing image onto a reference person. Generative adversarial network involves three modules semantic generation, cloth wrapping and try on module