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We present a multimodal learning-based method to simultaneously synthesize co-speech facial expressions and upper-body gestures for digital characters using RGB video data captured using commodity cameras. Our approach learns from sparse…

Computer Vision and Pattern Recognition · Computer Science 2024-11-26 Uttaran Bhattacharya , Aniket Bera , Dinesh Manocha

Co-speech gesture generation is to synthesize a gesture sequence that not only looks real but also matches with the input speech audio. Our method generates the movements of a complete upper body, including arms, hands, and the head.…

Computer Vision and Pattern Recognition · Computer Science 2021-11-30 Shenhan Qian , Zhi Tu , Yihao Zhi , Wen Liu , Shenghua Gao

Existing gesture generation methods primarily focus on upper body gestures based on audio features, neglecting speech content, emotion, and locomotion. These limitations result in stiff, mechanical gestures that fail to convey the true…

Sound · Computer Science 2026-03-10 Yongkang Cheng , Mingjiang Liang , Shaoli Huang , Gaoge Han , Jifeng Ning , Wei Liu

Real-time interactive video-chat portraits have been increasingly recognized as the future trend, particularly due to the remarkable progress made in text and voice chat technologies. However, existing methods primarily focus on real-time…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Jinwei Qi , Chaonan Ji , Sheng Xu , Peng Zhang , Bang Zhang , Liefeng Bo

Real-time synthesis of high-fidelity 3D character motion from audio is a pivotal component for next-generation interactive avatars and virtual assistants. However, most existing approaches are limited to offline processing of complete audio…

Computer Vision and Pattern Recognition · Computer Science 2026-05-28 Bohong Chen , Yumeng Li , Yinglin Xu , Youyi Zheng , Yanlin Weng , Kun Zhou

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

Although significant progress has been made to audio-driven talking face generation, existing methods either neglect facial emotion or cannot be applied to arbitrary subjects. In this paper, we propose the Emotion-Aware Motion Model (EAMM)…

Computer Vision and Pattern Recognition · Computer Science 2022-09-26 Xinya Ji , Hang Zhou , Kaisiyuan Wang , Qianyi Wu , Wayne Wu , Feng Xu , Xun Cao

This paper introduces Stereo-Talker, a novel one-shot audio-driven human video synthesis system that generates 3D talking videos with precise lip synchronization, expressive body gestures, temporally consistent photo-realistic quality, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xiang Deng , Youxin Pang , Xiaochen Zhao , Chao Xu , Lizhen Wang , Hongjiang Xiao , Shi Yan , Hongwen Zhang , Yebin Liu

We propose EMAGE, a framework to generate full-body human gestures from audio and masked gestures, encompassing facial, local body, hands, and global movements. To achieve this, we first introduce BEAT2 (BEAT-SMPLX-FLAME), a new mesh-level…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Haiyang Liu , Zihao Zhu , Giorgio Becherini , Yichen Peng , Mingyang Su , You Zhou , Xuefei Zhe , Naoya Iwamoto , Bo Zheng , Michael J. Black

Recent diffusion-based talking face generation models have demonstrated impressive potential in synthesizing videos that accurately match a speech audio clip with a given reference identity. However, existing approaches still encounter…

Computer Vision and Pattern Recognition · Computer Science 2025-10-16 Xingpei Ma , Jiaran Cai , Yuansheng Guan , Shenneng Huang , Qiang Zhang , Shunsi Zhang

Whenever we speak, our voice is accompanied by facial movements and expressions. Several recent works have shown the synthesis of highly photo-realistic videos of talking faces, but they either require a source video to drive the target…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Prateek Manocha , Prithwijit Guha

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Audio-driven talking-head generation has advanced rapidly with diffusion-based generative models, yet producing temporally coherent videos with fine-grained motion control remains challenging. We propose DEMO, a flow-matching generative…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Peiyin Chen , Zhuowei Yang , Hui Feng , Sheng Jiang , Rui Yan

Co-speech gesture generation is crucial for automatic digital avatar animation. However, existing methods suffer from issues such as unstable training and temporal inconsistency, particularly in generating high-fidelity and comprehensive…

Computer Vision and Pattern Recognition · Computer Science 2023-08-30 Longbin Ji , Pengfei Wei , Yi Ren , Jinglin Liu , Chen Zhang , Xiang Yin

This paper investigates a novel task of talking face video generation solely from speeches. The speech-to-video generation technique can spark interesting applications in entertainment, customer service, and human-computer-interaction…

Sound · Computer Science 2021-07-15 Shijing Si , Jianzong Wang , Xiaoyang Qu , Ning Cheng , Wenqi Wei , Xinghua Zhu , Jing Xiao

Emotional talking head synthesis aims to generate talking portrait videos with vivid expressions. Existing methods still exhibit limitations in control flexibility, motion naturalness, and expression quality. Moreover, currently available…

Computer Vision and Pattern Recognition · Computer Science 2025-12-24 Yiguo Jiang , Xiaodong Cun , Yong Zhang , Yudian Zheng , Fan Tang , Chi-Man Pun

The domain of 3D talking head generation has witnessed significant progress in recent years. A notable challenge in this field consists in blending speech-related motions with expression dynamics, which is primarily caused by the lack of…

Computer Vision and Pattern Recognition · Computer Science 2025-06-10 Federico Nocentini , Claudio Ferrari , Stefano Berretti

Generating vivid and emotional 3D co-speech gestures is crucial for virtual avatar animation in human-machine interaction applications. While the existing methods enable generating the gestures to follow a single emotion label, they…

Computer Vision and Pattern Recognition · Computer Science 2024-03-28 Xingqun Qi , Jiahao Pan , Peng Li , Ruibin Yuan , Xiaowei Chi , Mengfei Li , Wenhan Luo , Wei Xue , Shanghang Zhang , Qifeng Liu , Yike Guo

In this paper, we introduce a simple and novel framework for one-shot audio-driven talking head generation. Unlike prior works that require additional driving sources for controlled synthesis in a deterministic manner, we instead…

Graphics · Computer Science 2022-12-09 Zhentao Yu , Zixin Yin , Deyu Zhou , Duomin Wang , Finn Wong , Baoyuan Wang

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