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Related papers: Fashion-VDM: Video Diffusion Model for Virtual Try…

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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

Virtual try-off (VTOFF) aims to recover canonical flat-garment representations from images of dressed persons for standardized display and downstream virtual try-on. Prior methods often treat VTOFF as direct image translation driven by…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Shuang Liu , Ao Yu , Linkang Cheng , Xiwen Huang , Li Zhao , Junhui Liu , Zhiting Lin , Yu Liu

Virtual Try-On (VTON) is a transformative technology in e-commerce and fashion design, enabling realistic digital visualization of clothing on individuals. In this work, we propose VTON 360, a novel 3D VTON method that addresses the open…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Zijian He , Yuwei Ning , Yipeng Qin , Guangrun Wang , Sibei Yang , Liang Lin , Guanbin Li

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

Diffusion models, widely used for image and video generation, face a significant limitation: the risk of memorizing and reproducing training data during inference, potentially generating unauthorized copyrighted content. While prior…

Computer Vision and Pattern Recognition · Computer Science 2025-04-28 Chen Chen , Enhuai Liu , Daochang Liu , Mubarak Shah , Chang Xu

Diffusion generative models have recently become a powerful technique for creating and modifying high-quality, coherent video content. This survey provides a comprehensive overview of the critical components of diffusion models for video…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Andrew Melnik , Michal Ljubljanac , Cong Lu , Qi Yan , Weiming Ren , Helge Ritter

Realistic temporal dynamics are crucial for many video generation, processing and modelling applications, e.g. in computational fluid dynamics, weather prediction, or long-term climate simulations. Video diffusion models (VDMs) are the…

Machine Learning · Computer Science 2025-05-16 Philipp Hess , Maximilian Gelbrecht , Christof Schötz , Michael Aich , Yu Huang , Shangshang Yang , Niklas Boers

This paper presents a learning-based clothing animation method for highly efficient virtual try-on simulation. Given a garment, we preprocess a rich database of physically-based dressed character simulations, for multiple body shapes and…

Computer Vision and Pattern Recognition · Computer Science 2019-03-19 Igor Santesteban , Miguel A. Otaduy , Dan Casas

Image-based Virtual Try-On (VTON) techniques rely on either supervised in-shop approaches, which ensure high fidelity but struggle with cross-domain generalization, or unsupervised in-the-wild methods, which improve adaptability but remain…

Computer Vision and Pattern Recognition · Computer Science 2025-07-22 Zhaotong Yang , Yuhui Li , Shengfeng He , Xinzhe Li , Yangyang Xu , Junyu Dong , Yong Du

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 is a promising application of computer graphics and human computer interaction that can have a profound real-world impact especially during this pandemic. Existing image-based works try to synthesize a try-on image from a…

Graphics · Computer Science 2021-09-13 Toby Chong , I-Chao Shen , Nobuyuki Umetani , Takeo Igarashi

Existing 4D human datasets fall short for fashion-specific research, lacking either realistic garment dynamics or task-specific annotations. Synthetic datasets suffer from a realism gap, whereas real-world captures lack the detailed…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Hunor Laczkó , Libang Jia , Loc-Phat Truong , Diego Hernández , Sergio Escalera , Jordi Gonzalez , Meysam Madadi

In this paper, we propose the first diffusion-based all-in-one video restoration method that utilizes the power of a pre-trained Stable Diffusion and a fine-tuned ControlNet. Our method can restore various types of video degradation with a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Yizhou Li , Zihua Liu , Yusuke Monno , Masatoshi Okutomi

Image-based 3D Virtual Try-ON (VTON) aims to sculpt the 3D human according to person and clothes images, which is data-efficient (i.e., getting rid of expensive 3D data) but challenging. Recent text-to-3D methods achieve remarkable…

Computer Vision and Pattern Recognition · Computer Science 2024-07-24 Zhenyu Xie , Haoye Dong , Yufei Gao , Zehua Ma , Xiaodan Liang

We present Stable Video Diffusion - a latent video diffusion model for high-resolution, state-of-the-art text-to-video and image-to-video generation. Recently, latent diffusion models trained for 2D image synthesis have been turned into…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Andreas Blattmann , Tim Dockhorn , Sumith Kulal , Daniel Mendelevitch , Maciej Kilian , Dominik Lorenz , Yam Levi , Zion English , Vikram Voleti , Adam Letts , Varun Jampani , Robin Rombach

Diffusion models have made significant strides in image generation, mastering tasks such as unconditional image synthesis, text-image translation, and image-to-image conversions. However, their capability falls short in the realm of video…

Computer Vision and Pattern Recognition · Computer Science 2024-12-10 Gaurav Shrivastava , Abhinav Shrivastava

Given a person and a garment image, virtual try-on (VTO) aims to synthesize a realistic image of the person wearing the garment, while preserving their original pose and identity. Although recent VTO methods excel at visualizing garment…

Computer Vision and Pattern Recognition · Computer Science 2026-04-10 Johanna Karras , Yuanhao Wang , Yingwei Li , Ira Kemelmacher-Shlizerman

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

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

We present a novel task called online video editing, which is designed to edit \textbf{streaming} frames while maintaining temporal consistency. Unlike existing offline video editing assuming all frames are pre-established and accessible,…

Computer Vision and Pattern Recognition · Computer Science 2024-05-31 Feng Chen , Zhen Yang , Bohan Zhuang , Qi Wu
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