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

Connected Papers

Building similarity graph...

Analyzing shared references across papers

Discussion

Authors

Nishchay Sinha

Pinank Trivedi

Yashraj Verma

Actions

References and Citations

Connected Papers

Building similarity graph...

Analyzing shared references across papers

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

Key Points

Abstract

Citation Network

Connected Papers

Discussion

Authors

Actions

References and Citations

Citation Network

Connected Papers

Discussion

Cite this study