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

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Using image models naively for solving inverse video problems often suffers from flickering, texture-sticking, and temporal inconsistency in generated videos. To tackle these problems, in this paper, we view frames as continuous functions…

Computer Vision and Pattern Recognition · Computer Science 2024-10-23 Giannis Daras , Weili Nie , Karsten Kreis , Alex Dimakis , Morteza Mardani , Nikola Borislavov Kovachki , Arash Vahdat

In this paper, we present DreaMoving, a diffusion-based controllable video generation framework to produce high-quality customized human videos. Specifically, given target identity and posture sequences, DreaMoving can generate a video of…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Mengyang Feng , Jinlin Liu , Kai Yu , Yuan Yao , Zheng Hui , Xiefan Guo , Xianhui Lin , Haolan Xue , Chen Shi , Xiaowen Li , Aojie Li , Xiaoyang Kang , Biwen Lei , Miaomiao Cui , Peiran Ren , Xuansong Xie

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

Diffusion models have revolutionized generative modeling, enabling unprecedented realism in image and video synthesis. This success has sparked interest in leveraging their representations for visual understanding tasks. While recent works…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Pedro Vélez , Luisa F. Polanía , Yi Yang , Chuhan Zhang , Rishabh Kabra , Anurag Arnab , Mehdi S. M. Sajjadi

We present FloodDiffusion, a new framework for text-driven, streaming human motion generation. Given time-varying text prompts, FloodDiffusion generates text-aligned, seamless motion sequences with real-time latency. Unlike existing methods…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Yiyi Cai , Yuhan Wu , Kunhang Li , You Zhou , Bo Zheng , Haiyang Liu

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

Despite the rapid advancement of Virtual Try-On (VTON) and Try-Off (VTOFF) technologies, existing VTON methods face challenges with fine-grained detail preservation, generalization to complex scenes, complicated pipeline, and efficient…

Computer Vision and Pattern Recognition · Computer Science 2026-03-25 Weixuan Zeng , Pengcheng Wei , Huaiqing Wang , Boheng Zhang , Jia Sun , Dewen Fan , Lin HE , Long Chen , Qianqian Gan , Fan Yang , Tingting Gao

Reconstructing 3D clothed humans from monocular images and videos is a fundamental problem with applications in virtual try-on, avatar creation, and mixed reality. Despite significant progress in human body recovery, accurately…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Yingxuan You , Ren Li , Corentin Dumery , Cong Cao , Hao Li , Pascal Fua

The rapid development of diffusion models (DMs) has significantly advanced image and video applications, making "what you want is what you see" a reality. Among these, video editing has gained substantial attention and seen a swift rise in…

Computer Vision and Pattern Recognition · Computer Science 2024-07-11 Wenhao Sun , Rong-Cheng Tu , Jingyi Liao , Dacheng Tao

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

Visual relation detection (VRD) aims to identify relationships (or interactions) between object pairs in an image. Although recent VRD models have achieved impressive performance, they are all restricted to pre-defined relation categories,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-17 Kaifeng Gao , Siqi Chen , Hanwang Zhang , Jun Xiao , Yueting Zhuang , Qianru Sun

Virtual try-on methods aim to generate images of fashion models wearing arbitrary combinations of garments. This is a challenging task because the generated image must appear realistic and accurately display the interaction between…

Computer Vision and Pattern Recognition · Computer Science 2021-06-15 Kedan Li , Min jin Chong , Jeffrey Zhang , Jingen Liu

Recently, latent diffusion models has demonstrated promising performance in real-world video super-resolution (VSR) task, which can reconstruct high-quality videos from distorted low-resolution input through multiple diffusion steps.…

Computer Vision and Pattern Recognition · Computer Science 2025-09-23 Hanting Li , Huaao Tang , Jianhong Han , Tianxiong Zhou , Jiulong Cui , Haizhen Xie , Yan Chen , Jie Hu

Despite the remarkable process of talking-head-based avatar-creating solutions, directly generating anchor-style videos with full-body motions remains challenging. In this study, we propose Make-Your-Anchor, a novel system necessitating…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Ziyao Huang , Fan Tang , Yong Zhang , Xiaodong Cun , Juan Cao , Jintao Li , Tong-Yee Lee

Long video generation remains a challenging and compelling topic in computer vision. Diffusion based models, among the various approaches to video generation, have achieved state of the art quality with their iterative denoising procedures.…

Computer Vision and Pattern Recognition · Computer Science 2025-03-14 Siyang Zhang , Harry Yang , Ser-Nam Lim

Virtual Try-On (VTON) has become a crucial tool in ecommerce, enabling the realistic simulation of garments on individuals while preserving their original appearance and pose. Early VTON methods relied on single generative networks, but…

Computer Vision and Pattern Recognition · Computer Science 2025-01-10 Shuliang Ning , Yipeng Qin , Xiaoguang Han

Video diffusion models have achieved impressive realism and controllability but are limited by high computational demands, restricting their use on mobile devices. This paper introduces the first mobile-optimized video diffusion model.…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Haitam Ben Yahia , Denis Korzhenkov , Ioannis Lelekas , Amir Ghodrati , Amirhossein Habibian

Significant advancements have been achieved in the realm of large-scale pre-trained text-to-video Diffusion Models (VDMs). However, previous methods either rely solely on pixel-based VDMs, which come with high computational costs, or on…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 David Junhao Zhang , Jay Zhangjie Wu , Jia-Wei Liu , Rui Zhao , Lingmin Ran , Yuchao Gu , Difei Gao , Mike Zheng Shou

Image-based Virtual Try-ON aims to transfer an in-shop garment onto a specific person. Existing methods employ a global warping module to model the anisotropic deformation for different garment parts, which fails to preserve the semantic…

Computer Vision and Pattern Recognition · Computer Science 2023-03-27 Zhenyu Xie , Zaiyu Huang , Xin Dong , Fuwei Zhao , Haoye Dong , Xijin Zhang , Feida Zhu , Xiaodan Liang

Generating high-quality videos that synthesize desired realistic content is a challenging task due to their intricate high-dimensionality and complexity of videos. Several recent diffusion-based methods have shown comparable performance by…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Kihong Kim , Haneol Lee , Jihye Park , Seyeon Kim , Kwanghee Lee , Seungryong Kim , Jaejun Yoo