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Diffusion-based image translation guided by semantic texts or a single target image has enabled flexible style transfer which is not limited to the specific domains. Unfortunately, due to the stochastic nature of diffusion models, it is…

Computer Vision and Pattern Recognition · Computer Science 2023-02-02 Gihyun Kwon , Jong Chul Ye

Image-based virtual try-on is challenging in fitting a target in-shop clothes into a reference person under diverse human poses. Previous works focus on preserving clothing details ( e.g., texture, logos, patterns ) when transferring…

Computer Vision and Pattern Recognition · Computer Science 2022-10-18 Bingwen Hu , Ping Liu , Zhedong Zheng , Mingwu Ren

We present an image-based VIirtual Try-On Network (VITON) without using 3D information in any form, which seamlessly transfers a desired clothing item onto the corresponding region of a person using a coarse-to-fine strategy. Conditioned…

Computer Vision and Pattern Recognition · Computer Science 2018-06-14 Xintong Han , Zuxuan Wu , Zhe Wu , Ruichi Yu , Larry S. Davis

This paper introduces ITA-MDT, the Image-Timestep-Adaptive Masked Diffusion Transformer Framework for Image-Based Virtual Try-On (IVTON), designed to overcome the limitations of previous approaches by leveraging the Masked Diffusion…

Computer Vision and Pattern Recognition · Computer Science 2025-06-03 Ji Woo Hong , Tri Ton , Trung X. Pham , Gwanhyeong Koo , Sunjae Yoon , Chang D. Yoo

Diffusion models (DMs) have become the new trend of generative models and have demonstrated a powerful ability of conditional synthesis. Among those, text-to-image diffusion models pre-trained on large-scale image-text pairs are highly…

Computer Vision and Pattern Recognition · Computer Science 2023-03-06 Wenliang Zhao , Yongming Rao , Zuyan Liu , Benlin Liu , Jie Zhou , Jiwen Lu

Video try-on stands as a promising area for its tremendous real-world potential. Previous research on video try-on has primarily focused on transferring product clothing images to videos with simple human poses, while performing poorly with…

Computer Vision and Pattern Recognition · Computer Science 2025-07-29 Jun Zheng , Jing Wang , Fuwei Zhao , Xujie Zhang , Xiaodan Liang

We introduce DiffusionTrend for virtual fashion try-on, which forgoes the need for retraining diffusion models. Using advanced diffusion models, DiffusionTrend harnesses latent information rich in prior information to capture the nuances of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Wengyi Zhan , Mingbao Lin , Shuicheng Yan , Rongrong Ji

Latest advances have achieved realistic virtual try-on (VTON) through localized garment inpainting using latent diffusion models, significantly enhancing consumers' online shopping experience. However, existing VTON technologies neglect the…

Computer Vision and Pattern Recognition · Computer Science 2024-08-07 Fei Shen , Xin Jiang , Xin He , Hu Ye , Cong Wang , Xiaoyu Du , Zechao Li , Jinhui Tang

Diffusion models enable high-quality virtual try-on (VTO) with their established image synthesis abilities. Despite the extensive end-to-end training of large pre-trained models involved in current VTO methods, real-world applications often…

Computer Vision and Pattern Recognition · Computer Science 2025-09-18 Xingzi Xu , Qi Li , Shuwen Qiu , Julien Han , Karim Bouyarmane

Virtual try-on systems have long been hindered by heavy reliance on human body masks, limited fine-grained control over garment attributes, and poor generalization to real-world, in-the-wild scenarios. In this paper, we propose JCo-MVTON…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Aowen Wang , Wei Li , Hao Luo , Mengxing Ao , Chenyu Zhu , Xinyang Li , Fan Wang

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

Virtual try-on (VTON) has been widely explored for rendering garments onto person images, while its inverse task, virtual try-off (VTOFF), remains largely overlooked. VTOFF aims to recover standardized product images of garments directly…

Computer Vision and Pattern Recognition · Computer Science 2026-02-24 Davide Lobba , Fulvio Sanguigni , Bin Ren , Marcella Cornia , Rita Cucchiara , Nicu Sebe

Given a pair of images depicting a person and a garment separately, image-based 3D virtual try-on methods aim to reconstruct a 3D human model that realistically portrays the person wearing the desired garment. In this paper, we present…

Computer Vision and Pattern Recognition · Computer Science 2025-01-28 Xiaojing Zhong , Zhonghua Wu , Xiaofeng Yang , Guosheng Lin , Qingyao Wu

Computer vision is transforming fashion industry through Virtual Try-On (VTON) and Virtual Try-Off (VTOFF). VTON generates images of a person in a specified garment using a target photo and a standardized garment image, while a more…

Computer Vision and Pattern Recognition · Computer Science 2025-07-14 Riza Velioglu , Petra Bevandic , Robin Chan , Barbara Hammer

We present Fashion-VDM, a video diffusion model (VDM) for generating virtual try-on videos. Given an input garment image and person video, our method aims to generate a high-quality try-on video of the person wearing the given garment,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Johanna Karras , Yingwei Li , Nan Liu , Luyang Zhu , Innfarn Yoo , Andreas Lugmayr , Chris Lee , Ira Kemelmacher-Shlizerman

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…

Computer Vision and Pattern Recognition · Computer Science 2025-07-23 Zheng Wang , Xianbing Sun , Shengyi Wu , Jiahui Zhan , Jianlou Si , Chi Zhang , Liqing Zhang , Jianfu Zhang

This paper proposes a novel garment transfer method supervised with knowledge distillation from virtual try-on. Our method first reasons the transfer parsing to provide shape prior to downstream tasks. We employ a multi-phase teaching…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Naiyu Fang , Lemiao Qiu , Shuyou Zhang , Zili Wang , Kerui Hu , Jianrong Tan

Recent advances in diffusion models have significantly elevated the visual fidelity of Virtual Try-On (VTON) systems, yet reliable evaluation remains a persistent bottleneck. Traditional metrics struggle to quantify fine-grained texture…

Computer Vision and Pattern Recognition · Computer Science 2026-05-07 Jin Li , Tao Chen , Shuai Jiang , Weijie Wang , Jingwen Luo , Chenhui Wu

The idea of \textit{Virtual Try-ON} (VTON) benefits e-retailing by giving an user the convenience of trying a clothing at the comfort of their home. In general, most of the existing VTON methods produce inconsistent results when a person…

Computer Vision and Pattern Recognition · Computer Science 2024-01-09 Debapriya Roy , Sanchayan Santra , Diganta Mukherjee , Bhabatosh Chanda

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