Future of Fashion: AI-Powered Virtual Dressing for E-Commerce Applications

This paper introduces an innovative AI-powered Virtual Dressing technology designed to revolutionize the way consumers shop for clothing online. Utilizing advanced computer vision techniques and machine learning models, our system offers a seamless virtual dressing experience. The process begins with high-resolution image capture, followed by dynamic resizing for optimal processing. A sophisticated cloth segmentation method is employed to accurately identify and separate the clothing item from the background. Utilizing the models for cloth segmentation and semantic segmentation, combined with posing coordinates, our system ensures precise body posture and garment alignment. The removal of background elements is achieved through semantic segmentation masks, enhancing the realism of the virtual experience. The final virtual dressing visualization supports both scenarios of retaining or omitting the background, based on user preference. To assess consumer interest in such technology, we conducted a survey which revealed that a vast majority of online shoppers would consider buying clothing if they could see a virtual picture of themselves in the attire beforehand. This finding underscores the potential of our AI -powered Virtual Dressing technology to not only enhance the online shopping experience by providing a realistic visualization of clothing fit but also significantly reduce return rates due to size or fit dissatisfaction. Our experiments demonstrate the system's efficacy in creating realistic and customizable virtual dressing experiences, showcasing its potential to become an integral part of future e-commerce platforms.