Abstract
In today’s world, fashion has become intricately linked to personal identity and cultural expression, with clothing choices varying significantly across individuals based on factors such as body structure, gender, social influences, and geographic background. While traditional shopping at brick-and-mortar stores allows customers to physically try on garments, this experience can often be time-consuming and limited by the availability of fitting rooms, leading to inconvenience and frustration. With the rapid expansion of online shopping plat- forms, consumers now seek more realistic and interactive ways to evaluate clothing virtually, yet existing systems frequently fall short of providing an immersive, tactile experience. This gap results in higher dissatisfaction, inaccurate visualizations, and increased product returns due to poor fit or misrepresentation of garments. To address these issues, this research introduces an advanced Virtual Fitting Room (VFR) system that leverages cutting-edge deep learning techniques, including Deep Neural Networks (DNNs) and Generative Adversarial Networks (GANs), within a two-dimensional framework to enable highly realistic virtual try-on experiences. The proposed system incorporates sophisticated computer vision methods, such as precise image segmentation, garment warping, and fabric behavior simulation, to create a natural, seamless inter- action wherein users can see how clothing appears on virtual avatars with remarkable accuracy. By focusing on realistic garment overlays that adapt to various body shapes and poses, this platform delivers an immersive environment that closely mimics physical fitting experiences, thereby enhancing user engagement and confidence. Implementing this technology not only improves customer satisfaction by providing a more authentic and visually appealing visualization but also reduces the likelihood of returns caused by mismatched expectations. Ultimately, this innovative approach contributes to a more sustainable and technologically advanced fashion retail ecosystem, transforming online clothing shopping into a more enjoyable and reliable process while addressing the needs of modern consumers and retailers alike.
Keywords
Virtual Dressing Room, Deep Neural Networks, 2D Virtual Try-On, Human Pose Estimation, Clothing Transformation, Generative AI Models, Image Processing, Online Fashion Commerce, Visual Computing Techniques, Fashion Technology Innovation
Citations
IRE Journals:
Harshita G C, Hityshi C M, Trisha V, Bhoomika Venkatesh Gouda "An Enhanced Virtual Fitting Room Using Deep Neural Network" Iconic Research And Engineering Journals Volume 9 Issue 6 2025 Page 76-80 https://doi.org/10.64388/IREV9I6-1712538
IEEE:
Harshita G C, Hityshi C M, Trisha V, Bhoomika Venkatesh Gouda
"An Enhanced Virtual Fitting Room Using Deep Neural Network" Iconic Research And Engineering Journals, 9(6) https://doi.org/10.64388/IREV9I6-1712538
About IRE Journals
IRE Journals is an open access online journals established with an aim to publish high quality of research work in various diciplines. We have more than 6 years in publications. Over 2500+ papers already published.
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