StageAttn-VTON: Stage-Wise Flow Deformation with Attention for High-Resolution Virtual Try-On

Virtual try-on is a key enabling technology for online fashion retail and digital garment visualization. It aims to realistically render a target garment on a person while preserving geometric alignment and fine texture details. Appearance flow-based approaches provide explicit deformation modeling but often suffer from texture squeezing and boundary artifacts in challenging scenarios, such as long sleeves and tucked-in garments, especially under high-resolution settings. In this work, we propose StageAttn-VTON (Stage-wise Attentive Virtual Try-On), an appearance flow-based framework that improves structural coherence and visual fidelity through stage-wise deformation modeling. Specifically, garment warping is decomposed into three stages—coarse alignment, local refinement, and non-target region removal—which mitigates the coupling between competing objectives, such as smooth texture preservation and accurate structural alignment. Furthermore, we introduce a self-attention module in the image synthesis stage to enhance global dependency modeling and capture long-range garment–body interactions. Experiments on VITON-HD and the upper-body subset of DressCode demonstrate that StageAttn-VTON achieves consistently strong performance against representative warping-based and diffusion-based baselines. In addition, qualitative comparisons show that the proposed method better alleviates deformation artifacts in challenging regions such as sleeves and waist areas.