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The body movements accompanying speech aid speakers in expressing their ideas. Co-speech motion generation is one of the important approaches for synthesizing realistic avatars. Due to the intricate correspondence between speech and motion,…

Multimedia · Computer Science 2024-08-28 Sen Wang , Jiangning Zhang , Xin Tan , Zhifeng Xie , Chengjie Wang , Lizhuang Ma

Audio-driven co-speech human gesture generation has made remarkable advancements recently. However, most previous works only focus on single person audio-driven gesture generation. We aim at solving the problem of conversational co-speech…

Human-Computer Interaction · Computer Science 2024-01-12 Haiwei Xue , Sicheng Yang , Zhensong Zhang , Zhiyong Wu , Minglei Li , Zonghong Dai , Helen Meng

Current approaches for 3D human motion synthesis generate high quality animations of digital humans performing a wide variety of actions and gestures. However, a notable technological gap exists in addressing the complex dynamics of multi…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Anindita Ghosh , Rishabh Dabral , Vladislav Golyanik , Christian Theobalt , Philipp Slusallek

Audio-driven cospeech video generation typically involves two stages: speech-to-gesture and gesture-to-video. While significant advances have been made in speech-to-gesture generation, synthesizing natural expressions and gestures remains…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Renda Li , Xiaohua Qi , Qiang Ling , Jun Yu , Ziyi Chen , Peng Chang , Mei HanJing Xiao

Generating realistic human-human interactions is a challenging task that requires not only high-quality individual body and hand motions, but also coherent coordination among all interactants. Due to limitations in available data and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-30 Pablo Ruiz-Ponce , Sergio Escalera , José García-Rodríguez , Jiankang Deng , Rolandos Alexandros Potamias

Co-speech gestures, if presented in the lively form of videos, can achieve superior visual effects in human-machine interaction. While previous works mostly generate structural human skeletons, resulting in the omission of appearance…

Computer Vision and Pattern Recognition · Computer Science 2024-04-03 Xu He , Qiaochu Huang , Zhensong Zhang , Zhiwei Lin , Zhiyong Wu , Sicheng Yang , Minglei Li , Zhiyi Chen , Songcen Xu , Xiaofei Wu

Recent advances in co-speech gesture and talking head generation have been impressive, yet most methods focus on only one of the two tasks. Those that attempt to generate both often rely on separate models or network modules, increasing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Steven Hogue , Chenxu Zhang , Yapeng Tian , Xiaohu Guo

Full-body gestures play a pivotal role in natural interactions and are crucial for achieving effective communication. Nevertheless, most existing studies primarily focus on the gesture generation of speakers, overlooking the vital role of…

Graphics · Computer Science 2025-05-09 Jinhe Huang , Yongkang Cheng , Yuming Hang , Gaoge Han , Jinewei Li , Jing Zhang , Xingjian Gu

We have recently seen tremendous progress in diffusion advances for generating realistic human motions. Yet, they largely disregard the multi-human interactions. In this paper, we present InterGen, an effective diffusion-based approach that…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Han Liang , Wenqian Zhang , Wenxuan Li , Jingyi Yu , Lan Xu

Modeling and generating human reactions poses a significant challenge with broad applications for computer vision and human-computer interaction. Existing methods either treat multiple individuals as a single entity, directly generating…

Computer Vision and Pattern Recognition · Computer Science 2025-09-30 Xiyan Xu , Sirui Xu , Yu-Xiong Wang , Liang-Yan Gui

Synthesizing synchronized and natural co-speech gesture videos remains a formidable challenge. Recent approaches have leveraged motion graphs to harness the potential of existing video data. To retrieve an appropriate trajectory from the…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yafei Song , Peng Zhang , Bang Zhang

Recent advancements in diffusion models have significantly improved the realism and generalizability of character-driven animation, enabling the synthesis of high-quality motion from just a single RGB image and a set of driving poses.…

Computer Vision and Pattern Recognition · Computer Science 2025-12-02 Alireza Javanmardi , Pragati Jaiswal , Tewodros Amberbir Habtegebrial , Christen Millerdurai , Shaoxiang Wang , Alain Pagani , Didier Stricker

We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length. While previous works focused on co-speech gesture or expression generation individually, the joint…

Sound · Computer Science 2024-04-09 Junming Chen , Yunfei Liu , Jianan Wang , Ailing Zeng , Yu Li , Qifeng Chen

Diffusion models have experienced a surge of interest as highly expressive yet efficiently trainable probabilistic models. We show that these models are an excellent fit for synthesising human motion that co-occurs with audio, e.g., dancing…

Machine Learning · Computer Science 2023-05-17 Simon Alexanderson , Rajmund Nagy , Jonas Beskow , Gustav Eje Henter

Generating realistic human motions that naturally respond to both spoken language and physical objects is crucial for interactive digital experiences. Current methods, however, address speech-driven gestures or object interactions…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Sreehari Rajan , Kunal Bhosikar , Charu Sharma

Current co-speech motion generation approaches usually focus on upper body gestures following speech contents only, while lacking supporting the elaborate control of synergistic full-body motion based on text prompts, such as talking while…

Computer Vision and Pattern Recognition · Computer Science 2024-10-02 Bohong Chen , Yumeng Li , Yao-Xiang Ding , Tianjia Shao , Kun Zhou

We tackle the challenging task of generating complete 3D facial animations for two interacting, co-located participants from a mixed audio stream. While existing methods often produce disembodied "talking heads" akin to a video conference…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Mengyi Shan , Shouchieh Chang , Ziqian Bai , Shichen Liu , Yinda Zhang , Luchuan Song , Rohit Pandey , Sean Fanello , Zeng Huang

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

We address the problem of accurate capture and expressive modelling of interactive behaviors happening between two persons in daily scenarios. Different from previous works which either only consider one person or focus on conversational…

Computer Vision and Pattern Recognition · Computer Science 2024-05-28 Yinghao Huang , Leo Ho , Dafei Qin , Mingyi Shi , Taku Komura

Gestures play a key role in human communication. Recent methods for co-speech gesture generation, while managing to generate beat-aligned motions, struggle generating gestures that are semantically aligned with the utterance. Compared to…

Computer Vision and Pattern Recognition · Computer Science 2024-03-27 Muhammad Hamza Mughal , Rishabh Dabral , Ikhsanul Habibie , Lucia Donatelli , Marc Habermann , Christian Theobalt
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