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A Virtual Try-On Method based on Enhanced Feature Representation and Global Attention

Yuanyuan Li
International Core Journal of Engineering, (2026), Vol.12, No.3, pp.386-396
Published: March 19, 2026
DOI: 10.6919/ICJE.202603_12(3).0044
PDF: Download Full Text PDF
Abstract

Virtual try-on (VTON) synthesizes realistic images by mapping a target garment onto a person while preserving structural alignment and texture fidelity. Existing methods often struggle with complex garment deformations and fine-grained details, causing artifacts such as distortions and texture loss. To address these challenges, we propose EAG-VTON, a framework combining enhanced feature representation and global attention. Specifically, we introduce an Enhanced Appearance Flow Warping Module (EAFWM) that integrates pre-activation residual blocks and an enhanced semantic-adaptive normalization (E-SPADE) to improve garment deformation accuracy. For image synthesis, a Residual Generator with Global Attention (RGC) combines ResNetV2 blocks with a Global Grouped Coordinate Attention (GGCA) module to capture long-range dependencies and preserve structural consistency. Experiments on the VITON-HD dataset show that EAG-VTON outperforms state-of-the-art baselines in SSIM, LPIPS, and FID, demonstrating superior structural fidelity and realistic texture reconstruction.

Keywords: Virtual Try-On; Garment Warping; Global Attention; Image Synthesis.
APA Citation: Yuanyuan Li (2026). A Virtual Try-On Method based on Enhanced Feature Representation and Global Attention. International Core Journal of Engineering, 12(3), 386-396. https://doi.org/10.6919/ICJE.202603_12(3).0044

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