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In face-to-face conversations, individuals need to switch between speaking and listening roles seamlessly. Existing 3D talking head generation models focus solely on speaking or listening, neglecting the natural dynamics of interactive…

Computer Vision and Pattern Recognition · Computer Science 2025-05-27 Ziqiao Peng , Yanbo Fan , Haoyu Wu , Xuan Wang , Hongyan Liu , Jun He , Zhaoxin Fan

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

3D Gaussian splatting-based talking head synthesis has recently gained attention for its ability to render high-fidelity images with real-time inference speed. However, since it is typically trained on only a short video that lacks the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-04 Junuk Cha , Seongro Yoon , Valeriya Strizhkova , Francois Bremond , Seungryul Baek

Recent advances in deep learning for sequential data have given rise to fast and powerful models that produce realistic videos of talking humans. The state of the art in talking face generation focuses mainly on lip-syncing, being…

Computer Vision and Pattern Recognition · Computer Science 2023-12-12 Georgios Milis , Panagiotis P. Filntisis , Anastasios Roussos , Petros Maragos

3D facial animation is often produced by manipulating facial deformation models (or rigs), that are traditionally parameterized by expression controls. A key component that is usually overlooked is expression 'style', as in, how a…

Computer Vision and Pattern Recognition · Computer Science 2024-01-30 Lingchen Yang , Gaspard Zoss , Prashanth Chandran , Paulo Gotardo , Markus Gross , Barbara Solenthaler , Eftychios Sifakis , Derek Bradley

Text-guided human body animation has advanced rapidly, yet facial animation lags due to the scarcity of well-annotated, text-paired facial corpora. To close this gap, we leverage foundation generative models to synthesize a large, balanced…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Luchuan Song , Pinxin Liu , Haiyang Liu , Zhenchao Jin , Yolo Yunlong Tang , Zichong Xu , Susan Liang , Jing Bi , Jason J Corso , Chenliang Xu

Current talking avatars mostly generate co-speech gestures based on audio and text of the utterance, without considering the non-speaking motion of the speaker. Furthermore, previous works on co-speech gesture generation have designed…

Multimedia · Computer Science 2024-01-09 Sicheng Yang , Zunnan Xu , Haiwei Xue , Yongkang Cheng , Shaoli Huang , Mingming Gong , Zhiyong Wu

Audio-Driven Face Animation is an eagerly anticipated technique for applications such as VR/AR, games, and movie making. With the rapid development of 3D engines, there is an increasing demand for driving 3D faces with audio. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-12-14 Haozhe Wu , Jia Jia , Junliang Xing , Hongwei Xu , Xiangyuan Wang , Jelo Wang

Audio-driven portrait animation aims to synthesize portrait videos that are conditioned by given audio. Animating high-fidelity and multimodal video portraits has a variety of applications. Previous methods have attempted to capture…

Computer Vision and Pattern Recognition · Computer Science 2023-07-20 Yunfei Liu , Lijian Lin , Fei Yu , Changyin Zhou , Yu Li

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

Audio-driven talking-head generation is a crucial and useful technology for virtual human interaction and film-making. While recent advances have focused on improving image fidelity and lip synchronization, generating accurate emotional…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Wenqing Wang , Yun Fu

Current audio-driven 3D head generation methods mainly focus on single-speaker scenarios, lacking natural, bidirectional listen-and-speak interaction. Achieving seamless conversational behavior, where speaking and listening states…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Lei Zhu , Lijian Lin , Ye Zhu , Jiahao Wu , Xuehan Hou , Yu Li , Yunfei Liu , Jie Chen

Implementing fine-grained emotion control is crucial for emotion generation tasks because it enhances the expressive capability of the generative model, allowing it to accurately and comprehensively capture and express various nuanced…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Guanwen Feng , Haoran Cheng , Yunan Li , Zhiyuan Ma , Chaoneng Li , Zhihao Qian , Qiguang Miao , Chi-Man Pun

In this work, we introduce the first autoregressive framework for real-time, audio-driven portrait animation, a.k.a, talking head. Beyond the challenge of lengthy animation times, a critical challenge in realistic talking head generation…

Computer Vision and Pattern Recognition · Computer Science 2025-03-25 Dingcheng Zhen , Shunshun Yin , Shiyang Qin , Hou Yi , Ziwei Zhang , Siyuan Liu , Gan Qi , Ming Tao

Generating talking face videos from audio attracts lots of research interest. A few person-specific methods can generate vivid videos but require the target speaker's videos for training or fine-tuning. Existing person-generic methods have…

Computer Vision and Pattern Recognition · Computer Science 2023-05-16 Weizhi Zhong , Chaowei Fang , Yinqi Cai , Pengxu Wei , Gangming Zhao , Liang Lin , Guanbin Li

Significant progress has been made in audio-driven human animation, while most existing methods focus mainly on facial movements, limiting their ability to create full-body animations with natural synchronization and fluidity. They also…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Qijun Gan , Ruizi Yang , Jianke Zhu , Shaofei Xue , Steven Hoi

Generating talking avatar driven by audio remains a significant challenge. Existing methods typically require high computational costs and often lack sufficient facial detail and realism, making them unsuitable for applications that demand…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yujian Liu , Shidang Xu , Jing Guo , Dingbin Wang , Zairan Wang , Xianfeng Tan , Xiaoli Liu

We propose an end to end deep learning approach for generating real-time facial animation from just audio. Specifically, our deep architecture employs deep bidirectional long short-term memory network and attention mechanism to discover the…

Machine Learning · Computer Science 2019-05-28 Guanzhong Tian , Yi Yuan , Yong liu

Synthesising 3D facial motion from speech is a crucial problem manifesting in a multitude of applications such as computer games and movies. Recently proposed methods tackle this problem in controlled conditions of speech. In this paper, we…

Computer Vision and Pattern Recognition · Computer Science 2019-04-16 Panagiotis Tzirakis , Athanasios Papaioannou , Alexander Lattas , Michail Tarasiou , Björn Schuller , Stefanos Zafeiriou

Talking head synthesis is a promising approach for the video production industry. Recently, a lot of effort has been devoted in this research area to improve the generation quality or enhance the model generalization. However, there are few…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Shuai Shen , Wenliang Zhao , Zibin Meng , Wanhua Li , Zheng Zhu , Jie Zhou , Jiwen Lu
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