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Speech-driven 3D facial animation has advanced rapidly, yet most approaches remain tied to registered template meshes, preventing effective deployment on raw 3D scans with arbitrary topology. At the same time, modeling controllable…

Computer Vision and Pattern Recognition · Computer Science 2026-03-17 Federico Nocentini , Thomas Besnier , Claudio Ferrari , Stefano Berretti , Mohamed Daoudi

Speech-driven 3D talking heads generation has emerged as a significant area of interest among researchers, presenting numerous challenges. Existing methods are constrained by animating faces with fixed topologies, wherein point-wise…

Computer Vision and Pattern Recognition · Computer Science 2024-09-26 Federico Nocentini , Thomas Besnier , Claudio Ferrari , Sylvain Arguillere , Stefano Berretti , Mohamed Daoudi

Despite exhibiting impressive performance in synthesizing lifelike personalized 3D talking heads, prevailing methods based on radiance fields suffer from high demands for training data and time for each new identity. This paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Jiahe Li , Jiawei Zhang , Xiao Bai , Jin Zheng , Jun Zhou , Lin Gu

Impressive progress has been made in audio-driven 3D facial animation recently, but synthesizing 3D talking-head with rich emotion is still unsolved. This is due to the lack of 3D generative models and available 3D emotional dataset with…

Computer Vision and Pattern Recognition · Computer Science 2021-04-27 Qianyun Wang , Zhenfeng Fan , Shihong Xia

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

We present a method that generates expressive talking heads from a single facial image with audio as the only input. In contrast to previous approaches that attempt to learn direct mappings from audio to raw pixels or points for creating…

Computer Vision and Pattern Recognition · Computer Science 2021-02-26 Yang Zhou , Xintong Han , Eli Shechtman , Jose Echevarria , Evangelos Kalogerakis , Dingzeyu Li

Audio-driven 3D talking avatar generation is increasingly important in virtual communication, digital humans, and interactive media, where avatars must preserve identity, synchronize lip motion with speech, express emotion, and exhibit…

Computer Vision and Pattern Recognition · Computer Science 2026-04-06 Zhongju Wang , Zhenhong Sun , Beier Wang , Yifu Wang , Daoyi Dong , Huadong Mo , Hongdong Li

The rapid advancement of large language models (LLMs) has significantly propelled the development of text-based chatbots, demonstrating their capability to engage in coherent and contextually relevant dialogues. However, extending these…

Computation and Language · Computer Science 2024-08-23 Yinghao Aaron Li , Xilin Jiang , Jordan Darefsky , Ge Zhu , Nima Mesgarani

Audio-driven talking head generation is a core component of digital avatars, and 3D Gaussian Splatting has shown strong performance in real-time rendering of high-fidelity talking heads. However, achieving precise control over fine-grained…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Shaoyang Xie , Xiaofeng Cong , Baosheng Yu , Zhipeng Gui , Jie Gui , Yuan Yan Tang , James Tin-Yau Kwok

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

Real-time talking head synthesis increasingly relies on deformable 3D Gaussian Splatting (3DGS) due to its low latency. Tri-planes are the standard choice for encoding Gaussians prior to deformation, since they provide a continuous domain…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Arpita Saggar , Jonathan C. Darling , Duygu Sarikaya , David C. Hogg

Although significant progress has been made in the field of speech-driven 3D facial animation recently, the speech-driven animation of an indispensable facial component, eye gaze, has been overlooked by recent research. This is primarily…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Yixiang Zhuang , Chunshan Ma , Yao Cheng , Xuan Cheng , Jing Liao , Juncong Lin

Audio-driven talking head generation holds significant potential for film production. While existing 3D methods have advanced motion modeling and content synthesis, they often produce rendering artifacts, such as motion blur, temporal…

Computer Vision and Pattern Recognition · Computer Science 2025-08-15 Kui Jiang , Shiyu Liu , Junjun Jiang , Hongxun Yao , Xiaopeng Fan

Human conversation involves continuous exchanges of speech and nonverbal cues such as head nods, gaze shifts, and facial expressions that convey attention and emotion. Modeling these bidirectional dynamics in 3D is essential for building…

Computer Vision and Pattern Recognition · Computer Science 2026-02-27 Junjie Chen , Fei Wang , Zhihao Huang , Qing Zhou , Kun Li , Dan Guo , Linfeng Zhang , Xun Yang

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

In this paper, we introduce a novel Face-to-Face spoken dialogue model. It processes audio-visual speech from user input and generates audio-visual speech as the response, marking the initial step towards creating an avatar chatbot system…

Computer Vision and Pattern Recognition · Computer Science 2024-08-05 Se Jin Park , Chae Won Kim , Hyeongseop Rha , Minsu Kim , Joanna Hong , Jeong Hun Yeo , Yong Man Ro

Although significant progress has been made in audio-driven talking head generation, text-driven methods remain underexplored. In this work, we present OmniTalker, a unified framework that jointly generates synchronized talking audio-video…

Computer Vision and Pattern Recognition · Computer Science 2025-06-04 Zhongjian Wang , Peng Zhang , Jinwei Qi , Guangyuan Wang , Chaonan Ji , Sheng Xu , Bang Zhang , Liefeng Bo

Talking face generation aims to synthesize realistic speaking portraits from a single image, yet existing methods often rely on explicit optical flow and local warping, which fail to model complex global motions and cause identity drift. We…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Bo Chen , Tao Liu , Qi Chen , Xie Chen , Zilong Zheng

The recent paradigm shift toward large reasoning models (LRMs) as autonomous agents has intensified the demand for sophisticated, multi-turn tool-use capabilities. Yet, existing datasets and data-generation approaches are limited by static,…

Computation and Language · Computer Science 2026-01-14 Jungho Cho , Minbyul Jeong , Sungrae Park

Speech-driven facial animation is the process that automatically synthesizes talking characters based on speech signals. The majority of work in this domain creates a mapping from audio features to visual features. This approach often…

Computer Vision and Pattern Recognition · Computer Science 2019-06-18 Konstantinos Vougioukas , Stavros Petridis , Maja Pantic