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Related papers: Learning to Generate Diverse Dance Motions with Tr…

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Group dance generation from music requires synchronizing multiple dancers while maintaining spatial coordination, making it highly relevant to applications such as film production, gaming, and animation. Recent group dance generation models…

Machine Learning · Computer Science 2026-03-25 Jing Xu , Weiqiang Wang , Cunjian Chen , Jun Liu , Qiuhong Ke

Urban scene synthesis with video generation models has recently shown great potential for autonomous driving. Existing video generation approaches to autonomous driving primarily focus on RGB video generation and lack the ability to support…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Guile Wu , David Huang , Dongfeng Bai , Bingbing Liu

Despite remarkable achievements in video synthesis, achieving granular control over complex dynamics, such as nuanced movement among multiple interacting objects, still presents a significant hurdle for dynamic world modeling, compounded by…

Computer Vision and Pattern Recognition · Computer Science 2024-03-21 Pengxiang Li , Kai Chen , Zhili Liu , Ruiyuan Gao , Lanqing Hong , Guo Zhou , Hua Yao , Dit-Yan Yeung , Huchuan Lu , Xu Jia

We present a novel method to generate human motion to populate 3D indoor scenes. It can be controlled with various combinations of conditioning signals such as a path in a scene, target poses, past motions, and scenes represented as 3D…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Nicolas Ugrinovic , Thomas Lucas , Fabien Baradel , Philippe Weinzaepfel , Gregory Rogez , Francesc Moreno-Noguer

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…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Jingwei Xu , Huazhe Xu , Bingbing Ni , Xiaokang Yang , Xiaolong Wang , Trevor Darrell

We introduce Multimodal DuetDance (MDD), a diverse multimodal benchmark dataset designed for text-controlled and music-conditioned 3D duet dance motion generation. Our dataset comprises 620 minutes of high-quality motion capture data…

Graphics · Computer Science 2025-08-26 Prerit Gupta , Jason Alexander Fotso-Puepi , Zhengyuan Li , Jay Mehta , Aniket Bera

Significant advancements in video diffusion models have brought substantial progress to the field of text-to-video (T2V) synthesis. However, existing T2V synthesis model struggle to accurately generate complex motion dynamics, leading to a…

Computer Vision and Pattern Recognition · Computer Science 2024-06-06 Haoran Cheng , Liang Peng , Linxuan Xia , Yuepeng Hu , Hengjia Li , Qinglin Lu , Xiaofei He , Boxi Wu

The pursuit of controllability as a higher standard of visual content creation has yielded remarkable progress in customizable image synthesis. However, achieving controllable video synthesis remains challenging due to the large variation…

Computer Vision and Pattern Recognition · Computer Science 2023-06-07 Xiang Wang , Hangjie Yuan , Shiwei Zhang , Dayou Chen , Jiuniu Wang , Yingya Zhang , Yujun Shen , Deli Zhao , Jingren Zhou

Ultrasound (US) is widely used for its advantages of real-time imaging, radiation-free and portability. In clinical practice, analysis and diagnosis often rely on US sequences rather than a single image to obtain dynamic anatomical…

Computer Vision and Pattern Recognition · Computer Science 2022-07-04 Jiamin Liang , Xin Yang , Yuhao Huang , Kai Liu , Xinrui Zhou , Xindi Hu , Zehui Lin , Huanjia Luo , Yuanji Zhang , Yi Xiong , Dong Ni

In the realm of motion generation, the creation of long-duration, high-quality motion sequences remains a significant challenge. This paper presents our groundbreaking work on "Infinite Motion", a novel approach that leverages long text to…

Computer Vision and Pattern Recognition · Computer Science 2024-07-15 Mengtian Li , Chengshuo Zhai , Shengxiang Yao , Zhifeng Xie , Keyu Chen , Yu-Gang Jiang

We introduce an approach for augmenting text-to-video generation models with customized motions, extending their capabilities beyond the motions depicted in the original training data. By leveraging a few video samples demonstrating…

Computer Vision and Pattern Recognition · Computer Science 2024-12-11 Joanna Materzynska , Josef Sivic , Eli Shechtman , Antonio Torralba , Richard Zhang , Bryan Russell

Diffusion models have demonstrated great success in text-to-video (T2V) generation. However, existing methods may face challenges when handling complex (long) video generation scenarios that involve multiple objects or dynamic changes in…

Computer Vision and Pattern Recognition · Computer Science 2024-10-15 Ye Tian , Ling Yang , Haotian Yang , Yuan Gao , Yufan Deng , Jingmin Chen , Xintao Wang , Zhaochen Yu , Xin Tao , Pengfei Wan , Di Zhang , Bin Cui

We present AIST++, a new multi-modal dataset of 3D dance motion and music, along with FACT, a Full-Attention Cross-modal Transformer network for generating 3D dance motion conditioned on music. The proposed AIST++ dataset contains 5.2 hours…

Computer Vision and Pattern Recognition · Computer Science 2021-08-03 Ruilong Li , Shan Yang , David A. Ross , Angjoo Kanazawa

With the rise of online dance-video platforms and rapid advances in AI-generated content (AIGC), music-driven dance generation has emerged as a compelling research direction. Despite substantial progress in related domains such as…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Kaixing Yang , Jiashu Zhu , Xulong Tang , Ziqiao Peng , Xiangyue Zhang , Puwei Wang , Jiahong Wu , Xiangxiang Chu , Hongyan Liu , Jun He

Understanding and predicting motion is a fundamental component of visual intelligence. Although modern video models exhibit strong comprehension of scene dynamics, exploring multiple possible futures through full video synthesis remains…

Computer Vision and Pattern Recognition · Computer Science 2026-04-14 Nick Stracke , Kolja Bauer , Stefan Andreas Baumann , Miguel Angel Bautista , Josh Susskind , Björn Ommer

The Future Internet is becoming a reality, providing a large-scale computing environments where a virtually infinite number of available services can be composed so to fit users' needs. Modern service-oriented applications will be more and…

Software Engineering · Computer Science 2015-12-25 Marco Autili , Amleto Di Salle , Alexander Perucci , Massimo Tivoli

The advancement of generative AI has extended to the realm of Human Dance Generation, demonstrating superior generative capacities. However, current methods still exhibit deficiencies in achieving spatiotemporal consistency, resulting in…

Computer Vision and Pattern Recognition · Computer Science 2023-10-24 Haipeng Fang , Zhihao Sun , Ziyao Huang , Fan Tang , Juan Cao , Sheng Tang

The rise of non-linear and interactive media such as video games has increased the need for automatic movement animation generation. In this survey, we review and analyze different aspects of building automatic movement generation systems…

Machine Learning · Computer Science 2019-03-21 Omid Alemi , Philippe Pasquier

Video sequences contain rich dynamic patterns, such as dynamic texture patterns that exhibit stationarity in the temporal domain, and action patterns that are non-stationary in either spatial or temporal domain. We show that a…

Machine Learning · Statistics 2017-05-31 Jianwen Xie , Song-Chun Zhu , Ying Nian Wu

Point tracking aims to follow visual points through complex motion, occlusion, and viewpoint changes, and has advanced rapidly with modern foundation models. Yet progress toward general point tracking remains constrained by limited…

Computer Vision and Pattern Recognition · Computer Science 2026-02-05 Weiguang Zhao , Haoran Xu , Xingyu Miao , Qin Zhao , Rui Zhang , Kaizhu Huang , Ning Gao , Peizhou Cao , Mingze Sun , Mulin Yu , Tao Lu , Linning Xu , Junting Dong , Jiangmiao Pang