What question did this study set out to answer?

The aim is to develop a virtual try-on system that accurately simulates clothing fit and drape using AI techniques.

April 12, 2026Open Access

AI-Powered Virtual Outfit Try-On System for Sustainable Fashion and Sizing Accuracy

Key Points

The aim is to develop a virtual try-on system that accurately simulates clothing fit and drape using AI techniques.
Developed DM-VTON, a diffusion-model-based virtual try-on system.
Utilized datasets VITON-HD and DressCode for training the model.
Integrated techniques like DensePose and semantic segmentation for garment rendering.
Designed a Gradio-based interface for high-resolution visualization.
Addressed challenges of occlusion handling and body shape variation.
Achieved high-quality, photo-realistic garment visualizations on diverse body shapes.
Effectively rendered clothing in varied poses and lighting conditions.
Enabled robust handling of both paired and unpaired virtual try-on scenarios.

Abstract

Abstract: This paper presents DM-VTON, a diffusion-model-based virtual try-on (VTON) system designed to generate high-quality, photo-realistic visualizations of clothing on human subjects. The system simulates how garments fit and drape on the human body under real-world conditions, accounting for diverse poses, lighting variations, and body shapes. It integrates advanced artificial intelligence techniques including diffusion models, IP-Adapters, DensePose, and semantic segmentation to achieve accurate and realistic garment rendering. The model was trained on benchmark datasets VITON-HD and DressCode, enabling robust handling of both paired and unpaired try-on scenarios. Key contributions include dense pose mapping, agnostic image generation, and a Gradio-based user interface supporting high-resolution inference at 1024×768 pixels. The modular and scalable architecture effectively tackles persistent challenges such as occlusion handling, body shape variation, and lighting inconsistency. This work advances the fields of virtual try-on, fashion synthesis, and AI-driven apparel visualization, with significant applicability to e-commerce, fashion design, and sustainable retail. Keywords: Virtual Try-On, Diffusion Models, DensePose, IP-Adapters, Semantic Segmentation, Fashion Synthesis, E-Commerce, Sustainable Fashion, Agnostic Image Generation, Garment Rendering. Title: AI-Powered Virtual Outfit Try-On System for Sustainable Fashion and Sizing Accuracy Author: Nishchay Sinha, Pinank Trivedi, Yashraj Verma, Deepak S. Shete International Journal of Electrical and Electronics Research ISSN 2348-6988 (online) Vol. 14, Issue 2, April 2026 - June 2026 Page No: 1-9 Research Publish Journals Website: www.researchpublish.com Published Date: 09-April-2026 DOI: https://doi.org/10.5281/zenodo.19483948 Paper Download Link (Source) https://www.researchpublish.com/papers/ai-powered-virtual-outfit-try-on-system-for-sustainable-fashion-and-sizing-accuracy

AI-Powered Virtual Outfit Try-On System for Sustainable Fashion and Sizing Accuracy

Key Points

Abstract

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