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Related papers: StyleMotif: Multi-Modal Motion Stylization using S…

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While recent text-to-video models excel at generating diverse scenes, they struggle with precise motion control, particularly for complex, multi-subject motions. Although methods for single-motion customization have been developed to…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Youcan Xu , Zhen Wang , Jiaxin Shi , Kexin Li , Feifei Shao , Jun Xiao , Yi Yang , Jun Yu , Long Chen

We build on the Visual Autoregressive Modeling (VAR) framework and formulate style transfer as conditional discrete sequence modeling in a learned latent space. Images are decomposed into multi-scale representations and tokenized into…

Computer Vision and Pattern Recognition · Computer Science 2026-05-13 Liqi Jing , Dingming Zhang , Peinian Li , Lichen Zhu , Yang Xu , Hanyu Xing

Arbitrary Style Transfer (AST) aims to transform images by adopting the style from any selected artwork. Nonetheless, the need to accommodate diverse and subjective user preferences poses a significant challenge. While some users wish to…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Dar-Yen Chen

Human motion style transfer allows characters to appear less rigidity and more realism with specific style. Traditional arbitrary image style transfer typically process mean and variance which is proved effective. Meanwhile, similar methods…

Computer Vision and Pattern Recognition · Computer Science 2025-11-07 Hanmo Chen , Chenghao Xu , Jiexi Yan , Cheng Deng

Recent advances in generative motion synthesis have enabled the production of realistic human motions from diverse input modalities. However, synthesizing compound actions from texts, which integrate multiple concurrent actions into…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Yue Jiang , Mingyu Yang , Liuyuxin Yang , Yang Xu , Bingxin Yun , Yuhe Zhang

Artistic image stylization aims to render the content provided by text or image with the target style, where content and style decoupling is the key to achieve satisfactory results. However, current methods for content and style…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Ma Zhuoqi , Zhang Yixuan , You Zejun , Tian Long , Liu Xiyang

The rapid development of generative diffusion models has significantly advanced the field of style transfer. However, most current style transfer methods based on diffusion models typically involve a slow iterative optimization process,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Feihong He , Gang Li , Fuhui Sun , Mengyuan Zhang , Lingyu Si , Xiaoyan Wang , Li Shen

Fashion design is a complex creative process that blends visual and textual expressions. Designers convey ideas through sketches, which define spatial structure and design elements, and textual descriptions, capturing material, texture, and…

Computer Vision and Pattern Recognition · Computer Science 2025-09-05 Federico Girella , Davide Talon , Ziyue Liu , Zanxi Ruan , Yiming Wang , Marco Cristani

Generating responses in a targeted style is a useful yet challenging task, especially in the absence of parallel data. With limited data, existing methods tend to generate responses that are either less stylized or less context-relevant. We…

Computation and Language · Computer Science 2019-09-13 Xiang Gao , Yizhe Zhang , Sungjin Lee , Michel Galley , Chris Brockett , Jianfeng Gao , Bill Dolan

Given an arbitrary content and style image, arbitrary style transfer aims to render a new stylized image which preserves the content image's structure and possesses the style image's style. Existing arbitrary style transfer methods are…

Computer Vision and Pattern Recognition · Computer Science 2025-05-14 Zhanjie Zhang , Quanwei Zhang , Junsheng Luan , Mengyuan Yang , Yun Wang , Lei Zhao

Animating stylized avatars with dynamic poses and expressions has attracted increasing attention for its broad range of applications. Previous research has made significant progress by training controllable generative models to synthesize…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Ken Chen , Sachith Seneviratne , Wei Wang , Dongting Hu , Sanjay Saha , Md. Tarek Hasan , Sanka Rasnayaka , Tamasha Malepathirana , Mingming Gong , Saman Halgamuge

Existing person video generation methods either lack the flexibility in controlling both the appearance and motion, or fail to preserve detailed appearance and temporal consistency. In this paper, we tackle the problem of motion transfer…

Computer Vision and Pattern Recognition · Computer Science 2019-08-13 Kun Cheng , Hao-Zhi Huang , Chun Yuan , Lingyiqing Zhou , Wei Liu

Recent neural style transfer frameworks have obtained astonishing visual quality and flexibility in Single-style Transfer (SST), but little attention has been paid to Multi-style Transfer (MST) which refers to simultaneously transferring…

Computer Vision and Pattern Recognition · Computer Science 2019-10-30 Zixuan Huang , Jinghuai Zhang , Jing Liao

This paper addresses the challenge of text-conditioned streaming motion generation, which requires us to predict the next-step human pose based on variable-length historical motions and incoming texts. Existing methods struggle to achieve…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lixing Xiao , Shunlin Lu , Huaijin Pi , Ke Fan , Liang Pan , Yueer Zhou , Ziyong Feng , Xiaowei Zhou , Sida Peng , Jingbo Wang

Compared to images, videos better reflect real-world acquisition and possess valuable temporal cues. However, existing multi-sensor fusion research predominantly integrates complementary context from multiple images rather than videos due…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Linfeng Tang , Yeda Wang , Meiqi Gong , Zizhuo Li , Yuxin Deng , Xunpeng Yi , Chunyu Li , Han Xu , Hao Zhang , Jiayi Ma

Recent research on motion generation has shown significant progress in generating semantically aligned motion with singular semantics. However, when employing these models to create composite sequences containing multiple semantically…

Multimedia · Computer Science 2025-10-17 Ho Yin Au , Jie Chen , Junkun Jiang , Jingyu Xiang

Fashion illustration is a crucial medium for designers to convey their creative vision and transform design concepts into tangible representations that showcase the interplay between clothing and the human body. In the context of fashion…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Alberto Baldrati , Davide Morelli , Marcella Cornia , Marco Bertini , Rita Cucchiara

Diffusion models arise as a powerful generative tool recently. Despite the great progress, existing diffusion models mainly focus on uni-modal control, i.e., the diffusion process is driven by only one modality of condition. To further…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Ziqi Huang , Kelvin C. K. Chan , Yuming Jiang , Ziwei Liu

Motion in-betweening, a fundamental task in character animation, consists of generating motion sequences that plausibly interpolate user-provided keyframe constraints. It has long been recognized as a labor-intensive and challenging…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Setareh Cohan , Guy Tevet , Daniele Reda , Xue Bin Peng , Michiel van de Panne

Our study introduces a new image-to-video generator called FashionFlow to generate fashion videos. By utilising a diffusion model, we are able to create short videos from still fashion images. Our approach involves developing and connecting…

Computer Vision and Pattern Recognition · Computer Science 2024-01-23 Tasin Islam , Alina Miron , XiaoHui Liu , Yongmin Li
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