تقرير
D$^4$-VTON: Dynamic Semantics Disentangling for Differential Diffusion based Virtual Try-On
| العنوان: | D$^4$-VTON: Dynamic Semantics Disentangling for Differential Diffusion based Virtual Try-On |
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| المؤلفون: | Yang, Zhaotong, Jiang, Zicheng, Li, Xinzhe, Zhou, Huiyu, Dong, Junyu, Zhang, Huaidong, Du, Yong |
| سنة النشر: | 2024 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
| الوصف: | In this paper, we introduce D$^4$-VTON, an innovative solution for image-based virtual try-on. We address challenges from previous studies, such as semantic inconsistencies before and after garment warping, and reliance on static, annotation-driven clothing parsers. Additionally, we tackle the complexities in diffusion-based VTON models when handling simultaneous tasks like inpainting and denoising. Our approach utilizes two key technologies: Firstly, Dynamic Semantics Disentangling Modules (DSDMs) extract abstract semantic information from garments to create distinct local flows, improving precise garment warping in a self-discovered manner. Secondly, by integrating a Differential Information Tracking Path (DITP), we establish a novel diffusion-based VTON paradigm. This path captures differential information between incomplete try-on inputs and their complete versions, enabling the network to handle multiple degradations independently, thereby minimizing learning ambiguities and achieving realistic results with minimal overhead. Extensive experiments demonstrate that D$^4$-VTON significantly outperforms existing methods in both quantitative metrics and qualitative evaluations, demonstrating its capability in generating realistic images and ensuring semantic consistency. Comment: ECCV2024 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2407.15111 |
| رقم الأكسشن: | edsarx.2407.15111 |
| قاعدة البيانات: | arXiv |
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