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Dynamic evolution behaviors of dimension-varying control systems often appear in the genetic regulatory network and the vehicle clutch system etc. An interesting and significant study on dimension-varying control systems is how to realize…

Optimization and Control · Mathematics 2023-03-02 Naqi Fan , Lijun Zhang

Controllability, temporal coherence, and detail synthesis remain the most critical challenges in video generation. In this paper, we focus on a commonly used yet underexplored cinematic technique known as Frame In and Frame Out.…

Computer Vision and Pattern Recognition · Computer Science 2025-10-27 Boyang Wang , Xuweiyi Chen , Matheus Gadelha , Zezhou Cheng

Animating human-scene interactions such as pick-and-place tasks in cluttered, complex layouts is a challenging task, with objects of a wide variation of geometries and articulation under scenarios with various obstacles. The main difficulty…

Graphics · Computer Science 2025-10-07 Jintao Lu , He Zhang , Yuting Ye , Takaaki Shiratori , Sebastian Starke , Taku Komura

The emergence of text-driven motion synthesis technique provides animators with great potential to create efficiently. However, in most cases, textual expressions only contain general and qualitative motion descriptions, while lack fine…

Computer Vision and Pattern Recognition · Computer Science 2023-12-27 Dong Wei , Xiaoning Sun , Huaijiang Sun , Bin Li , Shengxiang Hu , Weiqing Li , Jianfeng Lu

Objects that move in response to the actions of a main character often make an important contribution to the visual richness of an animated scene. We use the term "secondary motion" to refer to passive motions generated in response to the…

Graphics · Computer Science 2023-03-21 James F. O'Brien , Victor B. Zordan , Jessica K. Hodgins

In this work, we introduce an unconditional video generative model, InMoDeGAN, targeted to (a) generate high quality videos, as well as to (b) allow for interpretation of the latent space. For the latter, we place emphasis on interpreting…

Computer Vision and Pattern Recognition · Computer Science 2021-01-11 Yaohui Wang , Francois Bremond , Antitza Dantcheva

We present a new method for text-driven motion transfer - synthesizing a video that complies with an input text prompt describing the target objects and scene while maintaining an input video's motion and scene layout. Prior methods are…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Danah Yatim , Rafail Fridman , Omer Bar-Tal , Yoni Kasten , Tali Dekel

We present a probabilistic framework to generate character animations based on weak control signals, such that the synthesized motions are realistic while retaining the stochastic nature of human movement. The proposed architecture, which…

Graphics · Computer Science 2020-10-21 Saeed Ghorbani , Calden Wloka , Ali Etemad , Marcus A. Brubaker , Nikolaus F. Troje

This work aims to generate natural and diverse group motions of multiple humans from textual descriptions. While single-person text-to-motion generation is extensively studied, it remains challenging to synthesize motions for more than one…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Mengyi Shan , Lu Dong , Yutao Han , Yuan Yao , Tao Liu , Ifeoma Nwogu , Guo-Jun Qi , Mitch Hill

Generating stable and controllable character motion in real-time is a key challenge in computer animation. Existing methods often fail to provide fine-grained control or suffer from motion degradation over long sequences, limiting their use…

Computer Vision and Pattern Recognition · Computer Science 2025-12-05 Eunjong Lee , Eunhee Kim , Sanghoon Hong , Eunho Jung , Jihoon Kim

Image animation is a key task in computer vision which aims to generate dynamic visual content from static image. Recent image animation methods employ neural based rendering technique to generate realistic animations. Despite these…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Zuozhuo Dai , Zhenghao Zhang , Yao Yao , Bingxue Qiu , Siyu Zhu , Long Qin , Weizhi Wang

Text-driven human motion generation is an emerging task in animation and humanoid robot design. Existing algorithms directly generate the full sequence which is computationally expensive and prone to errors as it does not pay special…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Zichen Geng , Caren Han , Zeeshan Hayder , Jian Liu , Mubarak Shah , Ajmal Mian

Generating high-quality human interactions holds significant value for applications like virtual reality and robotics. However, existing methods often fail to preserve unique individual characteristics or fully adhere to textual…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Lipeng Wang , Hongxing Fan , Haohua Chen , Zehuan Huang , Lu Sheng

In this work, we present Conditional Adversarial Latent Models (CALM), an approach for generating diverse and directable behaviors for user-controlled interactive virtual characters. Using imitation learning, CALM learns a representation of…

Computer Vision and Pattern Recognition · Computer Science 2023-05-04 Chen Tessler , Yoni Kasten , Yunrong Guo , Shie Mannor , Gal Chechik , Xue Bin Peng

Robotic motion generation methods using machine learning have been studied in recent years. Bilateral control-based imitation learning can imitate human motions using force information. By means of this method, variable speed motion…

Robotics · Computer Science 2022-02-16 Yuki Saigusa , Ayumu Sasagawa , Sho Sakaino , Toshiaki Tsuji

This paper presents an approach to externally influencing a team of robots by means of time-varying density functions. These density functions represent rough references for where the robots should be located. To this end, a continuous-time…

Optimization and Control · Mathematics 2014-04-02 Sung G. Lee , Magnus Egerstedt

Human-human motion generation is essential for understanding humans as social beings. Current methods fall into two main categories: single-person-based methods and separate modeling-based methods. To delve into this field, we abstract the…

Computer Vision and Pattern Recognition · Computer Science 2026-03-11 Yabiao Wang , Shuo Wang , Jiangning Zhang , Ke Fan , Jiafu Wu , Zhucun Xue , Yong Liu

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…

Computer Vision and Pattern Recognition · Computer Science 2024-10-10 Nan Jiang , Zimo He , Zi Wang , Hongjie Li , Yixin Chen , Siyuan Huang , Yixin Zhu

Human motion is inherently diverse and semantically rich, while also shaped by the surrounding scene. However, existing motion generation approaches fail to generate semantically diverse motion while simultaneously respecting geometric…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Jungbin Cho , Minsu Kim , Jisoo Kim , Ce Zheng , Laszlo A. Jeni , Ming-Hsuan Yang , Youngjae Yu , Seonjoo Kim

Generating rich and controllable motion is a pivotal challenge in video synthesis. We propose Boximator, a new approach for fine-grained motion control. Boximator introduces two constraint types: hard box and soft box. Users select objects…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Jiawei Wang , Yuchen Zhang , Jiaxin Zou , Yan Zeng , Guoqiang Wei , Liping Yuan , Hang Li