OmniVTON++: Training-Free Universal Virtual Try-On with Principal Pose Guidance

• URL: http://arxiv.org/abs/2602.14552v1
• Date: Mon, 16 Feb 2026 08:27:43 GMT
• Title: OmniVTON++: Training-Free Universal Virtual Try-On with Principal Pose Guidance
• Authors: Zhaotong Yang, Yong Du, Shengfeng He, Yuhui Li, Xinzhe Li, Yangyang Xu, Junyu Dong, Jian Yang,
• Abstract summary: Image-based Virtual Try-On (VTON) concerns the synthesis of realistic person imagery through garment re-rendering under human pose and body constraints.<n>We present OmniVTON++, a training-free VTON framework designed for universal applicability.
• Score: 85.23143742905695
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Image-based Virtual Try-On (VTON) concerns the synthesis of realistic person imagery through garment re-rendering under human pose and body constraints. In practice, however, existing approaches are typically optimized for specific data conditions, making their deployment reliant on retraining and limiting their generalization as a unified solution. We present OmniVTON++, a training-free VTON framework designed for universal applicability. It addresses the intertwined challenges of garment alignment, human structural coherence, and boundary continuity by coordinating Structured Garment Morphing for correspondence-driven garment adaptation, Principal Pose Guidance for step-wise structural regulation during diffusion sampling, and Continuous Boundary Stitching for boundary-aware refinement, forming a cohesive pipeline without task-specific retraining. Experimental results demonstrate that OmniVTON++ achieves state-of-the-art performance across diverse generalization settings, including cross-dataset and cross-garment-type evaluations, while reliably operating across scenarios and diffusion backbones within a single formulation. In addition to single-garment, single-human cases, the framework supports multi-garment, multi-human, and anime character virtual try-on, expanding the scope of virtual try-on applications. The source code will be released to the public.

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