Realistic 3D Cloth Wearing Using AR/VR for Immersive Virtual Try-On in E-Commerce

Authors

  • Nikita Kanwar Department of Computer Science & Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India Author
  • Aditya Singh Department of Computer Science & Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India Author
  • Amita Sharma Department of Computer Science & Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India Author
  • Nishant Upadhyay Department of Computer Science & Engineering, School of Engineering and Technology, Sharda University, Greater Noida, India Author

Keywords:

Augmented Reality, Virtual Reality, 3D Clothing, Cloth Simulation, Virtual Try-On, Blender, Unity3D, Marvelous Designer

Abstract

This project, “Realistic 3D Cloth Wearing Using AR/VR for Immersive Virtual Try-On in E-commerce,” aims to transform online apparel shopping by enabling users to virtually try on clothes in real time. Traditional e-commerce struggles with inaccurate fit visualization, leading to dissatisfaction and high return rates. Our system tackles this through a pipeline of 3D body scanning, motion tracking, and physics-based cloth simulation to create lifelike avatars and realistic garment draping. Using AR, users can view outfits on themselves through mobile devices, while VR provides an immersive try-on experience. Machine learning enhances the platform with body measurement estimation, fit recommendations, and pose adaptability. The solution supports real-time garment swapping, large catalogues, and customization, improving user confidence and reducing retailer return costs. Beyond e-commerce, it has potential applications in virtual fashion shows, digital wardrobes, and sustainable retail.

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Published

13-03-2026

How to Cite

Kanwar, N. ., Singh, A., Sharma, A. ., & Upadhyay, N. . (2026). Realistic 3D Cloth Wearing Using AR/VR for Immersive Virtual Try-On in E-Commerce. DMPedia Lecture Notes in Multidisciplinary Research, IMPACT26, 338-346. https://digitalmanuscriptpedia.com/conferences/index.php/DMP-LNMR/article/view/106