3D Virtual Try-On (VTON) System Using Deep Learning and Physics-Based Simulation

Author(s)	Nidhi Kishor Raut, Pushkaraj Navnath Gaikwad, Soham Dnyaneshwar Gudewar
Country	India
Abstract	The growth of online fashion retail has created a rising demand for accurate, realistic, and personalized virtual try-on (VTON) systems. Traditional 2D VTON methods rely heavily on image warping, which limits realism and fails to capture natural garment draping behaviours. Recent advancements in 3D human modelling, geometric deep learning, and differentiable rendering have significantly changed this landscape. This paper provides a structured survey of enabling technologies, identifies fragmentation in existing approaches, and presents a comprehensive architecture for next-generation 3D virtual try-on systems. We propose a hybrid architecture combining deep learning (SMPL-X regression), geometric deep learning (GNN-based cloth deformation), and PyTorch3D physics-aware rendering to address the "integration gap" in current research.
Keywords	Virtual Try-On (VTON), SMPL-X, 3D Human Reconstruction, Graph Neural Networks (GNN), PyTorch3D, Cloth Simulation, Deep Learning, Geometric Deep Learning, Differentiable Rendering
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 8, Issue 1, January-February 2026
Published On	2026-02-10

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