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Related papers: GSTalker: Real-time Audio-Driven Talking Face Gene…

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This paper presents EGSTalker, a real-time audio-driven talking head generation framework based on 3D Gaussian Splatting (3DGS). Designed to enhance both speed and visual fidelity, EGSTalker requires only 3-5 minutes of training video to…

Sound · Computer Science 2025-10-13 Tianheng Zhu , Yinfeng Yu , Liejun Wang , Fuchun Sun , Wendong Zheng

We propose GaussianTalker, a novel framework for real-time generation of pose-controllable talking heads. It leverages the fast rendering capabilities of 3D Gaussian Splatting (3DGS) while addressing the challenges of directly controlling…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Kyusun Cho , Joungbin Lee , Heeji Yoon , Yeobin Hong , Jaehoon Ko , Sangjun Ahn , Seungryong Kim

Audio-driven talking head generation is crucial for applications in virtual reality, digital avatars, and film production. While NeRF-based methods enable high-fidelity reconstruction, they suffer from low rendering efficiency and…

Sound · Computer Science 2025-09-23 Tianheng Zhu , Yinfeng Yu , Liejun Wang , Fuchun Sun , Wendong Zheng

Recent works on audio-driven talking head synthesis using Neural Radiance Fields (NeRF) have achieved impressive results. However, due to inadequate pose and expression control caused by NeRF implicit representation, these methods still…

Computer Vision and Pattern Recognition · Computer Science 2024-08-12 Hongyun Yu , Zhan Qu , Qihang Yu , Jianchuan Chen , Zhonghua Jiang , Zhiwen Chen , Shengyu Zhang , Jimin Xu , Fei Wu , Chengfei Lv , Gang Yu

Speech-driven talking heads have recently emerged and enable interactive avatars. However, real-world applications are limited, as current methods achieve high visual fidelity but slow or fast yet temporally unstable. Diffusion methods…

Computer Vision and Pattern Recognition · Computer Science 2025-12-12 Madhav Agarwal , Mingtian Zhang , Laura Sevilla-Lara , Steven McDonagh

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

Radiance fields have demonstrated impressive performance in synthesizing lifelike 3D talking heads. However, due to the difficulty in fitting steep appearance changes, the prevailing paradigm that presents facial motions by directly…

Computer Vision and Pattern Recognition · Computer Science 2024-07-08 Jiahe Li , Jiawei Zhang , Xiao Bai , Jin Zheng , Xin Ning , Jun Zhou , Lin Gu

Most current audio-driven facial animation research primarily focuses on generating videos with neutral emotions. While some studies have addressed the generation of facial videos driven by emotional audio, efficiently generating…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Chuhang Ma , Shuai Tan , Ye Pan , Jiaolong Yang , Xin Tong

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

A key challenge in 3D talking head synthesis lies in the reliance on a long-duration talking head video to train a new model for each target identity from scratch. Recent methods have attempted to address this issue by extracting general…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Yuhang Guo , Kaijun Deng , Siyang Song , Jindong Xie , Wenhui Ma , Linlin Shen

We introduce an approach that creates animatable human avatars from monocular videos using 3D Gaussian Splatting (3DGS). Existing methods based on neural radiance fields (NeRFs) achieve high-quality novel-view/novel-pose image synthesis but…

Computer Vision and Pattern Recognition · Computer Science 2024-04-05 Zhiyin Qian , Shaofei Wang , Marko Mihajlovic , Andreas Geiger , Siyu Tang

We introduce GaussianSpeech, a novel approach that synthesizes high-fidelity animation sequences of photo-realistic, personalized 3D human head avatars from spoken audio. To capture the expressive, detailed nature of human heads, including…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Shivangi Aneja , Artem Sevastopolsky , Tobias Kirschstein , Justus Thies , Angela Dai , Matthias Nießner

Talking Head Generation aims at synthesizing natural-looking talking videos from speech and a single portrait image. Previous 3D talking head generation methods have relied on domain-specific heuristics such as warping-based facial motion…

Computer Vision and Pattern Recognition · Computer Science 2026-01-27 Tong Shi , Melonie de Almeida , Daniela Ivanova , Nicolas Pugeault , Paul Henderson

High-quality, real-time talking head synthesis remains a fundamental challenge in computer vision. Existing reconstruction- and rendering-based methods typically rely on identity-specific models, limiting cross-identity generalization. To…

Computer Vision and Pattern Recognition · Computer Science 2026-05-12 Peng Jia , Zhen Xiao , Jia Li , Xueliang Liu , Zhenzhen Hu , Lingyun Yu

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

Accurately synthesizing talking face videos and capturing fine facial features for individuals with long hair presents a significant challenge. To tackle these challenges in existing methods, we propose a decomposed per-embedding Gaussian…

Computer Vision and Pattern Recognition · Computer Science 2024-12-31 Kaijun Deng , Dezhi Zheng , Jindong Xie , Jinbao Wang , Weicheng Xie , Linlin Shen , Siyang Song

Talking head synthesis has emerged as a prominent research topic in computer graphics and multimedia, yet most existing methods often struggle to strike a balance between generation quality and computational efficiency, particularly under…

Graphics · Computer Science 2025-06-30 Shuai Shen , Wanhua Li , Yunpeng Zhang , Yap-Peng Tan , Jiwen Lu

Realistic 3D full-body talking avatars hold great potential in AR, with applications ranging from e-commerce live streaming to holographic communication. Despite advances in 3D Gaussian Splatting (3DGS) for lifelike avatar creation,…

Computer Vision and Pattern Recognition · Computer Science 2025-07-24 Jianchuan Chen , Jingchuan Hu , Gaige Wang , Zhonghua Jiang , Tiansong Zhou , Zhiwen Chen , Chengfei Lv

Implicit neural representation has paved the way for new approaches to dynamic scene reconstruction and rendering. Nonetheless, cutting-edge dynamic neural rendering methods rely heavily on these implicit representations, which frequently…

Computer Vision and Pattern Recognition · Computer Science 2023-11-22 Ziyi Yang , Xinyu Gao , Wen Zhou , Shaohui Jiao , Yuqing Zhang , Xiaogang Jin

Creating high-quality, generalizable speech-driven 3D talking heads remains a persistent challenge. Previous methods achieve satisfactory results for fixed viewpoints and small-scale audio variations, but they struggle with large head…

Computer Vision and Pattern Recognition · Computer Science 2025-07-11 Wentao Hu , Shunkai Li , Ziqiao Peng , Haoxian Zhang , Fan Shi , Xiaoqiang Liu , Pengfei Wan , Di Zhang , Hui Tian
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