Virtual Clothes Fitting: Leveraging Computer Vision and Deep Learning for a Seamless Online Shopping Experience

The digital transformation of the fashion industry has led to the surge of online shopping, but the absence of a virtual fitting room remains a significant challenge. Without the ability to try on clothes virtually, online shoppers may hesitate to make purchases due to concerns about fit, leading to higher return rates. To address this issue, researchers have proposed a virtual clothes fitting system that utilizes computer vision and deep learning. By employing the denoising diffusion probabilistic model (DDPM) developed in this research, consumers can virtually try on clothing, even those that are not physically available. The model’s effectiveness was evaluated through user feedback, and the proposed system emphasizes inclusivity by offering a wide range of clothing sizes and styles to cater to diverse body types and encourage a more inclusive online shopping experience.