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Diffusion models have led to the revolutionizing of generative modeling in numerous image synthesis tasks. Nevertheless, it is not trivial to directly apply diffusion models for synthesizing an image of a target person wearing a given…

Computer Vision and Pattern Recognition · Computer Science 2024-09-13 Siqi Wan , Yehao Li , Jingwen Chen , Yingwei Pan , Ting Yao , Yang Cao , Tao Mei

Diffusion models have shown preliminary success in virtual try-on (VTON) task. The typical dual-branch architecture comprises two UNets for implicit garment deformation and synthesized image generation respectively, and has emerged as the…

Computer Vision and Pattern Recognition · Computer Science 2025-05-23 Siqi Wan , Jingwen Chen , Yingwei Pan , Ting Yao , Tao Mei

Virtual try-on (VTON) transfers a target clothing image to a reference person, where clothing fidelity is a key requirement for downstream e-commerce applications. However, existing VTON methods still fall short in high-fidelity try-on due…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Han Yang , Yanlong Zang , Ziwei Liu

Existing image-based virtual try-on (VTON) methods primarily focus on single-layer or multi-garment VTON, neglecting multi-layer VTON (ML-VTON), which involves dressing multiple layers of garments onto the human body with realistic…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Yang Yu , Yunze Deng , Yige Zhang , Yanjie Xiao , Youkun Ou , Wenhao Hu , Mingchao Li , Bin Feng , Wenyu Liu , Dandan Zheng , Jingdong Chen

Recent advancements in Virtual Try-On (VTO) have demonstrated exceptional efficacy in generating realistic images and preserving garment details, largely attributed to the robust generative capabilities of text-to-image (T2I) diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhenchen Wan , Yanwu Xu , Zhaoqing Wang , Feng Liu , Tongliang Liu , Mingming Gong

Virtual try-on, which aims to seamlessly fit garments onto person images, has recently seen significant progress with diffusion-based models. However, existing methods commonly resort to duplicated backbones or additional image encoders to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-22 Haifeng Ni , Ming Xu

This study discusses the critical issues of Virtual Try-On in contemporary e-commerce and the prospective metaverse, emphasizing the challenges of preserving intricate texture details and distinctive features of the target person and the…

Computer Vision and Pattern Recognition · Computer Science 2024-07-18 Phuong Dam , Jihoon Jeong , Anh Tran , Daeyoung Kim

Diffusion-based virtual try-on methods achieve photorealistic synthesis through cross-attention mechanisms that transfer garment features to target body regions. However, these approaches rely on implicit learning of spatial…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Kosuke Takemoto , Takafumi Koshinaka

Virtual Try-On (VTON) has become a transformative technology, empowering users to experiment with fashion without ever having to physically try on clothing. However, existing methods often struggle with generating high-fidelity and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Ke Sun , Jian Cao , Qi Wang , Linrui Tian , Xindi Zhang , Lian Zhuo , Bang Zhang , Liefeng Bo , Wenbo Zhou , Weiming Zhang , Daiheng Gao

Image-based virtual try-on is challenging since the generated image should fit the garment to model images in various poses and keep the characteristics and details of the garment simultaneously. A popular research stream warps the garment…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Delong Zhang , Qiwei Huang , Yuanliu Liu , Yang Sun , Wei-Shi Zheng , Pengfei Xiong , Wei Zhang

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,…

Computer Vision and Pattern Recognition · Computer Science 2024-07-23 Zhaotong Yang , Zicheng Jiang , Xinzhe Li , Huiyu Zhou , Junyu Dong , Huaidong Zhang , Yong Du

Recent advancements in Virtual Try-On (VITON) have significantly improved image realism and garment detail preservation, driven by powerful text-to-image (T2I) diffusion models. However, existing methods often rely on user-provided masks,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-12 Zhenchen Wan , Yanwu xu , Dongting Hu , Weilun Cheng , Tianxi Chen , Zhaoqing Wang , Feng Liu , Tongliang Liu , Mingming Gong

Virtual Try-on (VTON) has become a core capability for online retail, where realistic try-on results provide reliable fit guidance, reduce returns, and benefit both consumers and merchants. Diffusion-based VTON methods achieve…

Computer Vision and Pattern Recognition · Computer Science 2026-03-13 Haohua Chen , Tianze Zhou , Wei Zhu , Runqi Wang , Yandong Guan , Dejia Song , Yibo Chen , Xu Tang , Yao Hu , Lu Sheng , Zhiyong Wu

Video try-on replaces clothing in videos with target garments. Existing methods struggle to generate high-quality and temporally consistent results when handling complex clothing patterns and diverse body poses. We present 3DV-TON, a novel…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Min Wei , Chaohui Yu , Jingkai Zhou , Fan Wang

Virtual try-on methods based on diffusion models achieve realistic try-on effects. They use an extra reference network or an additional image encoder to process multiple conditional image inputs, which adds complexity pre-processing and…

Computer Vision and Pattern Recognition · Computer Science 2025-01-13 Junsheng Luan , Guangyuan Li , Lei Zhao , Wei Xing

Virtual try-on is a promising computer vision topic with a high commercial value wherein a new garment is visually worn on a person with a photo-realistic effect. Previous studies conduct their shape and content inference at one stage,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Naiyu Fang , Lemiao Qiu , Shuyou Zhang , Zili Wang , Kerui Hu

Virtual try-on methods based on diffusion models achieve realistic effects but often require additional encoding modules, a large number of training parameters, and complex preprocessing, which increases the burden on training and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Zheng Chong , Xiao Dong , Haoxiang Li , Shiyue Zhang , Wenqing Zhang , Xujie Zhang , Hanqing Zhao , Dongmei Jiang , Xiaodan Liang

Virtual Try-On (VTON) technology allows users to visualize how clothes would look on them without physically trying them on, gaining traction with the rise of digitalization and online shopping. Traditional VTON methods, often using…

Computer Vision and Pattern Recognition · Computer Science 2025-01-14 Seohyun Lee , Jintae Park , Sanghyeok Park

Virtual try-on (VTON) has recently achieved impressive visual fidelity, but most existing systems require uploading personal photos to cloud-based GPUs, raising privacy concerns and limiting on-device deployment. To address this, we present…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Zhenchen Wan , Ce Chen , Runqi Lin , Jiaxin Huang , Tianxi Chen , Yanwu Xu , Tongliang Liu , Mingming Gong

The virtual try-on system has gained great attention due to its potential to give customers a realistic, personalized product presentation in virtualized settings. In this paper, we present PT-VTON, a novel pose-transfer-based framework for…

Computer Vision and Pattern Recognition · Computer Science 2021-11-25 Hanhan Zhou , Tian Lan , Guru Venkataramani