International Journal of Science, Engineering and TechnologyAuthors: Assistant Professor Mrs Ashwini Sawant, Ritika Gupta, Prajwal Shinde, Veena Suse, Siddhi Sali
Abstract: Virtual try-on technology has transformed online fashion retail by enabling users to visualize garments digitally, enhancing shopping confidence and reducing return rates. Modern Virtual try-on systems leverage deep learning, computer vision, and pose estimation to simulate realistic garment-person interactions. Early GAN-based methods faced limitations in garment deformation and identity preservation, whereas recent diffusion-based models, notably IDM-VTON, demonstrate superior image fidelity and adaptability. Benchmark datasets like VITON-HD and DressCode support objective evaluation using perceptual and semantic metrics. Despite substantial progress, challenges remain in modeling fine details, handling occlusion, and extending to multimodal and 2D representations. This study reviews key VTON components, emerging trends, and future research directions aimed at achieving more accurate, inclusive, and deployable virtual try-on solutions
DOI: https://
