APPLYING POSE-GUIDED DEEP LEARNING FOR REAL-TIME VIRTUAL TRY-ON

Author(s)	Dr. Chandrika J, Ms. Khushi K, Ms. Khalandar Bibi, Ms. Khushi H M, Ms. Moulya K A
Country	India
Abstract	This project presents a real-time virtual try-on system that applies pose-guided deep learning techniques to accurately fit and visualize clothing on a user’s 3D body model. Leveraging OpenCV for webcam capture, MediaPipe for real-time pose estimation, TensorFlow for size prediction, and Unity3D for interactive 3D visualization, the system enables users to virtually try on clothes with realistic fitting and 360° viewing capabilities. This seamless integration of cutting-edge computer vision and deep learning technologies enhances online shopping experiences by delivering personalized and engaging virtual try-ons.
Keywords	Virtual Try-On; Real-Time Pose Estimation; 3D Human Modeling; Size Prediction; GAN (PIFuHD); MediaPipe; VITON; Augmented Reality; Human-Computer Interaction; Fashion Technology
Field	Engineering
Published In	Volume 7, Issue 3, May-June 2025
Published On	2025-06-17
DOI	https://doi.org/10.36948/ijfmr.2025.v07i03.48017
Short DOI	https://doi.org/g9qqdj

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research