STM Journals Peer-reviewed research from Consortium e-Learning Network

E-Commerce for Future & Trends Review Article

E-Commerce Clothing Platform with Virtual Try-On

  1. Pratik Kape Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune
  2. Sarthak Joshi Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune
  3. Sujit Gawade Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune
  4. Satyajeet Babar Department of Computer Engineering, Parvatibai Genba Moze College of Engineering Wagholi, Pune

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

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