FW-VTON: Flattening-and-Warping for Person-to-Person Virtual Try-on

• URL: http://arxiv.org/abs/2507.16010v1
• Date: Mon, 21 Jul 2025 19:09:28 GMT
• Title: FW-VTON: Flattening-and-Warping for Person-to-Person Virtual Try-on
• Authors: Zheng Wang, Xianbing Sun, Shengyi Wu, Jiahui Zhan, Jianlou Si, Chi Zhang, Liqing Zhang, Jianfu Zhang,
• Abstract summary: This paper introduces a novel approach to the person-to-person try-on task.<n>Unlike the garment-to-person try-on task, the person-to-person task only involves two input images.<n>The goal is to generate a realistic combination of the target person with the desired garment.
• Score: 18.51680703943841
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Traditional virtual try-on methods primarily focus on the garment-to-person try-on task, which requires flat garment representations. In contrast, this paper introduces a novel approach to the person-to-person try-on task. Unlike the garment-to-person try-on task, the person-to-person task only involves two input images: one depicting the target person and the other showing the garment worn by a different individual. The goal is to generate a realistic combination of the target person with the desired garment. To this end, we propose Flattening-and-Warping Virtual Try-On (\textbf{FW-VTON}), a method that operates in three stages: (1) extracting the flattened garment image from the source image; (2) warping the garment to align with the target pose; and (3) integrating the warped garment seamlessly onto the target person. To overcome the challenges posed by the lack of high-quality datasets for this task, we introduce a new dataset specifically designed for person-to-person try-on scenarios. Experimental evaluations demonstrate that FW-VTON achieves state-of-the-art performance, with superior results in both qualitative and quantitative assessments, and also excels in garment extraction subtasks.

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