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We present GStalker, a 3D audio-driven talking face generation model with Gaussian Splatting for both fast training (40 minutes) and real-time rendering (125 FPS) with a 3$\sim$5 minute video for training material, in comparison with…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Bo Chen , Shoukang Hu , Qi Chen , Chenpeng Du , Ran Yi , Yanmin Qian , Xie Chen

Audio-driven talking head generation faces a fundamental trade-off between personalization and generalization, limiting its practical application. Implicit models often achieve generalization at the cost of structural incoherence, resulting…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Shiyu Liu , Kui Jiang , Junjun Jiang , Xianming Liu , Xiaocheng Feng , Hongxun Yao , Qi Tian

Speech-driven 3D facial animation aims to synthesize realistic facial motion sequences from given audio, matching the speaker's speaking style. However, previous works often require priors such as class labels of a speaker or additional 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-08-26 Hyung Kyu Kim , Sangmin Lee , Hak Gu Kim

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

Contemporary Human Computer Interaction (HCI) research relies primarily on neural network models for machine vision and speech understanding of a system user. Such models require extensively annotated training datasets for optimal…

Human-Computer Interaction · Computer Science 2023-11-14 Muhammad Ali Farooq , Dan Bigioi , Rishabh Jain , Wang Yao , Mariam Yiwere , Peter Corcoran

Diffusion models have recently advanced photorealistic human synthesis, although practical talking-head generation (THG) remains constrained by high inference latency, temporal instability such as flicker and identity drift, and imperfect…

Computer Vision and Pattern Recognition · Computer Science 2026-03-09 Soumya Mazumdar , Vineet Kumar Rakesh

Audio-driven talking head generation necessitates seamless integration of audio and visual data amidst the challenges posed by diverse input portraits and intricate correlations between audio and facial motions. In response, we propose a…

Computer Vision and Pattern Recognition · Computer Science 2024-12-16 Ziqi Zhou , Weize Quan , Hailin Shi , Wei Li , Lili Wang , Dong-Ming Yan

Recent advancements in speech-driven 3D talking head generation have made significant progress in lip synchronization. However, existing models still struggle to capture the perceptual alignment between varying speech characteristics and…

Graphics · Computer Science 2025-04-01 Lee Chae-Yeon , Oh Hyun-Bin , Han EunGi , Kim Sung-Bin , Suekyeong Nam , Tae-Hyun Oh

Generating talking head videos through a face image and a piece of speech audio still contains many challenges. ie, unnatural head movement, distorted expression, and identity modification. We argue that these issues are mainly because of…

Computer Vision and Pattern Recognition · Computer Science 2023-03-14 Wenxuan Zhang , Xiaodong Cun , Xuan Wang , Yong Zhang , Xi Shen , Yu Guo , Ying Shan , Fei Wang

Most earlier researches on talking face generation have focused on the synchronization of lip motion and speech content. However, head pose and facial emotions are equally important characteristics of natural faces. While audio-driven…

Computer Vision and Pattern Recognition · Computer Science 2024-11-05 Changpeng Cai , Guinan Guo , Jiao Li , Junhao Su , Fei Shen , Chenghao He , Jing Xiao , Yuanxu Chen , Lei Dai , Feiyu Zhu

The task of lip synchronization (lip-sync) seeks to match the lips of human faces with different audio. It has various applications in the film industry as well as for creating virtual avatars and for video conferencing. This is a…

Computer Vision and Pattern Recognition · Computer Science 2023-08-21 Soumik Mukhopadhyay , Saksham Suri , Ravi Teja Gadde , Abhinav Shrivastava

Despite numerous completed studies, achieving high fidelity talking face generation with highly synchronized lip movements corresponding to arbitrary audio remains a significant challenge in the field. The shortcomings of published studies…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Juan Zhang , Jiahao Chen , Cheng Wang , Zhiwang Yu , Tangquan Qi , Di Wu

Recent advances in diffusion models have led to significant progress in audio-driven lip synchronization. However, existing methods typically rely on constrained audio-visual alignment priors or multi-stage learning of intermediate…

Computer Vision and Pattern Recognition · Computer Science 2025-02-18 Junxian Ma , Shiwen Wang , Jian Yang , Junyi Hu , Jian Liang , Guosheng Lin , Jingbo chen , Kai Li , Yu Meng

While accurate lip synchronization has been achieved for arbitrary-subject audio-driven talking face generation, the problem of how to efficiently drive the head pose remains. Previous methods rely on pre-estimated structural information…

Computer Vision and Pattern Recognition · Computer Science 2021-04-23 Hang Zhou , Yasheng Sun , Wayne Wu , Chen Change Loy , Xiaogang Wang , Ziwei Liu

In this paper we introduce a new synchronisation task, Gesture-Sync: determining if a person's gestures are correlated with their speech or not. In comparison to Lip-Sync, Gesture-Sync is far more challenging as there is a far looser…

Computer Vision and Pattern Recognition · Computer Science 2023-10-10 Sindhu B Hegde , Andrew Zisserman

Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-fidelity and 3D-consistent novel-view frames. However, they…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jaehoon Ko , Kyusun Cho , Joungbin Lee , Heeji Yoon , Sangmin Lee , Sangjun Ahn , Seungryong Kim

Synthesizing high-fidelity and emotion-controllable talking video portraits, with audio-lip sync, vivid expressions, realistic head poses, and eye blinks, has been an important and challenging task in recent years. Most existing methods…

Computer Vision and Pattern Recognition · Computer Science 2025-03-28 Yibo Xia , Lizhen Wang , Xiang Deng , Xiaoyan Luo , Yunhong Wang , Yebin Liu

Lip sync has emerged as a promising technique for generating mouth movements from audio signals. However, synthesizing a high-resolution and photorealistic virtual news anchor is still challenging. Lack of natural appearance, visual…

Computer Vision and Pattern Recognition · Computer Science 2021-05-06 Ruobing Zheng , Zhou Zhu , Bo Song , Changjiang Ji

Virtual humans have gained considerable attention in numerous industries, e.g., entertainment and e-commerce. As a core technology, synthesizing photorealistic face frames from target speech and facial identity has been actively studied…

Audio-driven 3D talking head synthesis has advanced rapidly with Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS). By leveraging rich pre-trained priors, few-shot methods enable instant personalization from just a few seconds…

Computer Vision and Pattern Recognition · Computer Science 2026-03-31 Haolan Xu , Keli Cheng , Lei Wang , Ning Bi , Xiaoming Liu
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