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Styled online in-between motion generation has important application scenarios in computer animation and games. Its core challenge lies in the need to satisfy four critical requirements simultaneously: generation speed, motion quality,…

计算机视觉与模式识别 · 计算机科学 2023-06-22 Xiangjun Tang , Linjun Wu , He Wang , Bo Hu , Xu Gong , Yuchen Liao , Songnan Li , Qilong Kou , Xiaogang Jin

Motion style transfer is highly desired for motion generation systems for gaming. Compared to its offline counterpart, the research on online motion style transfer under interactive control is limited. In this work, we propose an end-to-end…

图形学 · 计算机科学 2022-03-31 Yingtian Tang , Jiangtao Liu , Cheng Zhou , Tingguang Li

Styled motion in-betweening is crucial for computer animation and gaming. However, existing methods typically encode motion styles by modeling whole-body motions, often overlooking the representation of individual body parts. This…

计算机视觉与模式识别 · 计算机科学 2025-08-14 Minyue Dai , Ke Fan , Bin Ji , Haoran Xu , Haoyu Zhao , Junting Dong , Jingbo Wang , Bo Dai

Human motion stylization aims to revise the style of an input motion while keeping its content unaltered. Unlike existing works that operate directly in pose space, we leverage the latent space of pretrained autoencoders as a more…

计算机视觉与模式识别 · 计算机科学 2024-02-27 Chuan Guo , Yuxuan Mu , Xinxin Zuo , Peng Dai , Youliang Yan , Juwei Lu , Li Cheng

Motion style transfer is a common method for enriching character animation. Motion style transfer algorithms are often designed for offline settings where motions are processed in segments. However, for online animation applications, such…

计算机视觉与模式识别 · 计算机科学 2022-03-30 Tianxin Tao , Xiaohang Zhan , Zhongquan Chen , Michiel van de Panne

We present a novel algorithm for transferring artistic styles of semantically meaningful local regions of an image onto local regions of a target video while preserving its photorealism. Local regions may be selected either fully…

计算机视觉与模式识别 · 计算机科学 2020-10-21 Xide Xia , Tianfan Xue , Wei-sheng Lai , Zheng Sun , Abby Chang , Brian Kulis , Jiawen Chen

We present StyleMotif, a novel Stylized Motion Latent Diffusion model, generating motion conditioned on both content and style from multiple modalities. Unlike existing approaches that either focus on generating diverse motion content or…

计算机视觉与模式识别 · 计算机科学 2025-03-31 Ziyu Guo , Young Yoon Lee , Joseph Liu , Yizhak Ben-Shabat , Victor Zordan , Mubbasir Kapadia

Synthesizing human motions in 3D environments, particularly those with complex activities such as locomotion, hand-reaching, and human-object interaction, presents substantial demands for user-defined waypoints and stage transitions. These…

计算机视觉与模式识别 · 计算机科学 2024-10-10 Nan Jiang , Zimo He , Zi Wang , Hongjie Li , Yixin Chen , Siyuan Huang , Yixin Zhu

Text-driven motion diffusion models are capable of generating realistic human motions, but text alone often struggles to express fine-level nuances of motion, commonly referred to as style. Recent approaches have tackled this challenge by…

计算机视觉与模式识别 · 计算机科学 2026-05-14 Junhyuk Jeon , Seokhyeon Hong , Junyong Noh

Neural style transfer is a powerful computer vision technique that can incorporate the artistic "style" of one image to the "content" of another. The underlying theory behind the approach relies on the assumption that the style of an image…

机器学习 · 计算机科学 2022-09-26 Yousef El-Laham , Svitlana Vyetrenko

Style transfer is a problem of rendering a content image in the style of another style image. A natural and common practical task in applications of style transfer is to adjust the strength of stylization. Algorithm of Gatys et al. (2016)…

计算机视觉与模式识别 · 计算机科学 2019-04-19 Victor Kitov

The production of animation is a resource intensive process in game companies. Therefore, techniques to synthesize animations have been developed. However, these procedural techniques offer limited adaptability by animation artists. In…

Generating diverse and natural human motion is one of the long-standing goals for creating intelligent characters in the animated world. In this paper, we propose a self-supervised method for generating long-range, diverse and plausible…

计算机视觉与模式识别 · 计算机科学 2020-08-25 Jingwei Xu , Huazhe Xu , Bingbing Ni , Xiaokang Yang , Xiaolong Wang , Trevor Darrell

Artistic style transfer is the problem of synthesizing an image with content similar to a given image and style similar to another. Although recent feed-forward neural networks can generate stylized images in real-time, these models produce…

计算机视觉与模式识别 · 计算机科学 2018-11-22 Mohammad Babaeizadeh , Golnaz Ghiasi

In this work, we proposed a new style-diverse dataset for the domain of motion style transfer. The motion dataset uses an industrial-standard human bone structure and thus is industry-ready to be plugged into 3D characters for many…

计算机视觉与模式识别 · 计算机科学 2023-07-11 Makito Kobayashi , Chen-Chieh Liao , Keito Inoue , Sentaro Yojima , Masafumi Takahashi

Generating realistic motions for digital humans is a core but challenging part of computer animations and games, as human motions are both diverse in content and rich in styles. While the latest deep learning approaches have made…

计算机视觉与模式识别 · 计算机科学 2022-12-19 Ziyi Chang , Edmund J. C. Findlay , Haozheng Zhang , Hubert P. H. Shum

Motions of virtual characters in movies or video games are typically generated by recording actors using motion capturing methods. Animations generated this way often need postprocessing, such as improving the periodicity of cyclic…

计算机视觉与模式识别 · 计算机科学 2015-02-27 Martin Bauer , Markus Eslitzbichler , Markus Grasmair

Motion style transfer changes the style of a motion while retaining its content and is useful in computer animations and games. Contact is an essential component of motion style transfer that should be controlled explicitly in order to…

计算机视觉与模式识别 · 计算机科学 2024-09-10 Xiangjun Tang , Linjun Wu , He Wang , Yiqian Wu , Bo Hu , Songnan Li , Xu Gong , Yuchen Liao , Qilong Kou , Xiaogang Jin

Image style transfer models based on convolutional neural networks usually suffer from high temporal inconsistency when applied to videos. Some video style transfer models have been proposed to improve temporal consistency, yet they fail to…

计算机视觉与模式识别 · 计算机科学 2018-11-02 Chang Gao , Derun Gu , Fangjun Zhang , Yizhou Yu

Change detection has been a challenging visual task due to the dynamic nature of real-world scenes. Good performance of existing methods depends largely on prior background images or a long-term observation. These methods, however, suffer…

计算机视觉与模式识别 · 计算机科学 2018-11-21 Chao Chen , Sheng Zhang , Cuibing Du
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