Summary of A Cost-efficient Approach For Creating Virtual Fitting Room Using Generative Adversarial Networks (gans), by Kirolos Attallah et al.
A Cost-Efficient Approach for Creating Virtual Fitting Room using Generative Adversarial Networks (GANs)
by Kirolos Attallah, Girgis Zaky, Nourhan Abdelrhim, Kyrillos Botros, Amjad Dife, Nermin Negied
First submitted to arxiv on: 1 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed virtual fitting room (VFR) is an AI-powered mobile application and webpage designed to enhance online clothing shopping experiences. By using Generative Adversarial Networks (GANs) and image processing techniques, the VFR generates a single output image from two input images – the person’s image and the cloth’s image. This technology allows customers to virtually try on clothes without physically trying them, reducing shopping time, crowding, and headaches in physical stores. From a business owner’s perspective, this project increases online sales and avoids product quality issues resulting from physical trials. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The VFR is an innovative solution for customers who prefer brick-and-mortar shopping experiences but have shifted to online shopping due to the COVID-19 pandemic. The AI-powered technology allows customers to virtually try on clothes, reducing uncertainty and hesitation when purchasing online. This convenient and time-saving experience will benefit both customers and business owners alike. |
