Degree
Master of Science in Data Science
Department
Department of Computer Science
Faculty/ School
School of Mathematics and Computer Science (SMCS)
Date of Submission
Spring 2024
Supervisor
Dr. Tariq Mahmood, Professor and Program Coordinator MS(CS) and MS(DS) Programs, School of Mathematics and Computer Science (SMCS)
Keywords
Generative AI, Latent Diffusion Model, OpenPose
Abstract
StyleSwap AI enhances virtual try-on experiences for online shoppers, addressing common challenges like uncertainty about fit and appearance. Traditional online shopping often leads to high return rates and customer dissatisfaction. By leveraging advanced AI techniques, StyleSwap AI offers a seamless and realistic virtual try-on experience, helping customers make more informed purchasing decisions and reducing return rates. This solution benefits both shoppers and fashion retailers by increasing convenience, boosting sales, and improving customer satisfaction and loyalty.
What sets StyleSwap AI apart is its advanced technology and unique features. Utilizing latent diffusion models and DensePose images, the project ensures accurate and realistic clothing placement. Additional features like ATV loss fine-tuning, comprehensive image processing, provide a superior virtual try-on experience. Clothing brands can save time and money on new clothing article photoshoots and marketing efforts, making StyleSwap AI a profitable and efficient solution in the market.
Document Type
Restricted Access
Submission Type
Research Project
Recommended Citation
Akbar, D. (2024). StyleSwap AI (Unpublished graduate research project). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/research-projects-msds/25
MSDS - End Sem. Progress.docx (9836 kB)
SwapStyleAI COLAB.ipynb (2382 kB)
MS Project Presentation.mp4 (105336 kB)
MSDS - Final Project Report.docx (15206 kB)
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