Shirt Virtual Try-On Comparison Dataset

In the current retail e-commerce industry, consumer demand for virtual try-on is increasing. However, existing technologies still face many challenges in image synthesis and user experience, such as poor image quality and unnatural synthesis effects. This dataset aims to address the current deficiencies in visual realism and user satisfaction by providing high-quality virtual shirt try-on images. The dataset construction process includes collecting user images from various angles, generating shirt images using deep learning techniques, and adopting a multi-round review and expert evaluation during annotation to ensure the quality and consistency of the data. The data storage format uses PNG and JPG for flexible application across different platforms. Strict quality control is applied to the data to ensure high precision and realism in image synthesis.