E-Commerce Clothing Platform with Virtual Try-On

Year : 2026 | Volume : 13 | Issue : 01 | Page : 17 24
    By

    Pratik Kape,

  • Sarthak Joshi,

  • Sujit Gawade,

  • Satyajeet Babar,

  1. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune, Maharashtra, India
  2. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune, Maharashtra, India
  3. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune, Maharashtra, India
  4. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune, Maharashtra, India

Abstract

The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to upload their images and digitally simulate selected garments using pose detection, semantic segmentation, geometric garment transformation, and adversarial image refinement techniques. MediaPipe is used for body landmark extraction, the U-Net architecture performs body region segmentation, and spatial transformation networks align garments with detected body structures. A generative adversarial network enhances the realism of the synthesized output. The platform is developed using the MERN (MongoDB, Express.js, React, and Node.js.) stack to ensure scalability, secure authentication, and efficient API communication. Experimental evaluation confirms that the integration of deep learning-based try-on functionality maintains acceptable response time while improving user personalization. The proposed solution demonstrates the feasibility of combining artificial intelligence with scalable web architecture to enhance digital apparel shopping experiences.

Keywords: Virtual try-on, AI in e-commerce, online clothing store, image processing, MERN stack, OpenCV, TensorFlow, personalized shopping, Razorpay integration, fashion recommendation system, responsive web design, user experience

[This article belongs to E-Commerce for Future & Trends ]

How to cite this article:
Pratik Kape, Sarthak Joshi, Sujit Gawade, Satyajeet Babar. E-Commerce Clothing Platform with Virtual Try-On. E-Commerce for Future & Trends. 2026; 13(01):17-24.
How to cite this URL:
Pratik Kape, Sarthak Joshi, Sujit Gawade, Satyajeet Babar. E-Commerce Clothing Platform with Virtual Try-On. E-Commerce for Future & Trends. 2026; 13(01):17-24. Available from: https://journals.stmjournals.com/ecft/article=2026/view=242161


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Regular Issue Subscription Review Article
Volume 13
Issue 01
Received 22/07/2025
Accepted 25/02/2026
Published 31/03/2026
Publication Time 252 Days
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