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Text-driven motion generation offers a powerful and intuitive way to create human movements directly from natural language. By removing the need for predefined motion inputs, it provides a flexible and accessible approach to controlling…

Computer Vision and Pattern Recognition · Computer Science 2025-05-15 Ali Rida Sahili , Najett Neji , Hedi Tabia

Our research presents a novel motion generation framework designed to produce whole-body motion sequences conditioned on multiple modalities simultaneously, specifically text and audio inputs. Leveraging Vector Quantized Variational…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Sohan Anisetty , James Hays

This work addresses the problem of generating 3D holistic body motions from human speech. Given a speech recording, we synthesize sequences of 3D body poses, hand gestures, and facial expressions that are realistic and diverse. To achieve…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Hongwei Yi , Hualin Liang , Yifei Liu , Qiong Cao , Yandong Wen , Timo Bolkart , Dacheng Tao , Michael J. Black

Text-driven human motion generation has recently attracted considerable attention, allowing models to generate human motions based on textual descriptions. However, current methods neglect the influence of human attributes-such as age,…

Computer Vision and Pattern Recognition · Computer Science 2025-11-14 Xinghan Wang , Kun Xu , Fei Li , Cao Sheng , Jiazhong Yu , Yadong Mu

Recent advances in text-driven human motion generation enable models to synthesize realistic motion sequences from natural language descriptions. However, most existing approaches assume identity-neutral motion and generate movements using…

Computer Vision and Pattern Recognition · Computer Science 2026-04-29 Wenqi Jia , Zekun Li , Abhay Mittal , Chengcheng Tang , Chuan Guo , Lezi Wang , James Matthew Rehg , Lingling Tao , Size An

The field has made significant progress in synthesizing realistic human motion driven by various modalities. Yet, the need for different methods to animate various body parts according to different control signals limits the scalability of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zixiang Zhou , Yu Wan , Baoyuan Wang

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

Long-term human motion can be represented as a series of motion modes---motion sequences that capture short-term temporal dynamics---with transitions between them. We leverage this structure and present a novel Motion Transformation…

Machine Learning · Computer Science 2018-08-15 Xinchen Yan , Akash Rastogi , Ruben Villegas , Kalyan Sunkavalli , Eli Shechtman , Sunil Hadap , Ersin Yumer , Honglak Lee

Co-speech gesture generation aims to synthesize realistic body movements that are semantically coherent with speech and faithful to a user-specified gestural style. Existing VQ-VAE based co-speech gesture generation methods improve…

Graphics · Computer Science 2026-05-11 Junchuan Zhao , Qifan Liang , Ye Wang

Generating conversational gestures from speech audio is challenging due to the inherent one-to-many mapping between audio and body motions. Conventional CNNs/RNNs assume one-to-one mapping, and thus tend to predict the average of all…

Computer Vision and Pattern Recognition · Computer Science 2021-08-17 Jing Li , Di Kang , Wenjie Pei , Xuefei Zhe , Ying Zhang , Zhenyu He , Linchao Bao

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…

Computer Vision and Pattern Recognition · Computer Science 2025-08-14 Minyue Dai , Ke Fan , Bin Ji , Haoran Xu , Haoyu Zhao , Junting Dong , Jingbo Wang , Bo Dai

Automatic gesture synthesis from speech is a topic that has attracted researchers for applications in remote communication, video games and Metaverse. Learning the mapping between speech and 3D full-body gestures is difficult due to the…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Kunkun Pang , Dafei Qin , Yingruo Fan , Julian Habekost , Takaaki Shiratori , Junichi Yamagishi , Taku Komura

This paper addresses the problem of generating 3D interactive human motion from text. Given a textual description depicting the actions of different body parts in contact with static objects, we synthesize sequences of 3D body poses that…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Sihan Ma , Qiong Cao , Jing Zhang , Dacheng Tao

Text-driven human motion generation in computer vision is both significant and challenging. However, current methods are limited to producing either deterministic or imprecise motion sequences, failing to effectively control the temporal…

Computer Vision and Pattern Recognition · Computer Science 2023-09-13 Yin Wang , Zhiying Leng , Frederick W. B. Li , Shun-Cheng Wu , Xiaohui Liang

The ability to synthesize long-term human motion sequences in real-world scenes can facilitate numerous applications. Previous approaches for scene-aware motion synthesis are constrained by pre-defined target objects or positions and thus…

Computer Vision and Pattern Recognition · Computer Science 2022-05-27 Jingbo Wang , Yu Rong , Jingyuan Liu , Sijie Yan , Dahua Lin , Bo Dai

Transferring human motion and appearance between videos of human actors remains one of the key challenges in Computer Vision. Despite the advances from recent image-to-image translation approaches, there are several transferring contexts…

Computer Vision and Pattern Recognition · Computer Science 2021-04-29 Thiago L. Gomes , Renato Martins , João Ferreira , Rafael Azevedo , Guilherme Torres , Erickson R. Nascimento

Generating videos of complex human motions such as flips, cartwheels, and martial arts remains challenging for current video diffusion models. Text-only conditioning is temporally ambiguous for fine-grained motion control, while explicit…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Ashkan Taghipour , Morteza Ghahremani , Zinuo Li , Hamid Laga , Farid Boussaid , Mohammed Bennamoun

This paper tackles the problem of physics-aware human motion synthesis in a dynamic scene. Unlike existing works which mainly tend to generate physically unrealistic motions due to limited contact modeling, typically restricted to hands, in…

Computer Vision and Pattern Recognition · Computer Science 2026-05-05 Chaoyue Xing , Wei Mao , Miaomiao Liu

Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods often rely on 3D motion capture data, which requires special setups, resulting in high costs…

Computer Vision and Pattern Recognition · Computer Science 2026-05-20 Ruoxi Guo , Huaijin Pi , Zehong Shen , Qing Shuai , Zechen Hu , Zhumei Wang , Yajiao Dong , Ruizhen Hu , Taku Komura , Sida Peng , Xiaowei Zhou

This work targets a novel text-driven whole-body motion generation task, which takes a given textual description as input and aims at generating high-quality, diverse, and coherent facial expressions, hand gestures, and body motions…

Computer Vision and Pattern Recognition · Computer Science 2023-10-20 Shunlin Lu , Ling-Hao Chen , Ailing Zeng , Jing Lin , Ruimao Zhang , Lei Zhang , Heung-Yeung Shum
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