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Audio-driven cospeech video generation typically involves two stages: speech-to-gesture and gesture-to-video. While significant advances have been made in speech-to-gesture generation, synthesizing natural expressions and gestures remains…

Computer Vision and Pattern Recognition · Computer Science 2025-04-14 Renda Li , Xiaohua Qi , Qiang Ling , Jun Yu , Ziyi Chen , Peng Chang , Mei HanJing Xiao

In this paper, we propose a talking face generation method that takes an audio signal as input and a short target video clip as reference, and synthesizes a photo-realistic video of the target face with natural lip motions, head poses, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Chenxu Zhang , Yifan Zhao , Yifei Huang , Ming Zeng , Saifeng Ni , Madhukar Budagavi , Xiaohu Guo

Audio-driven talking face generation has gained significant attention for applications in digital media and virtual avatars. While recent methods improve audio-lip synchronization, they often struggle with temporal consistency, identity…

Computer Vision and Pattern Recognition · Computer Science 2025-10-28 Fatemeh Nazarieh , Zhenhua Feng , Diptesh Kanojia , Muhammad Awais , Josef Kittler

Audio-driven talking head generation requires precise synchronization between facial animations and audio signals. This paper introduces ATL-Diff, a novel approach addressing synchronization limitations while reducing noise and…

Computer Vision and Pattern Recognition · Computer Science 2025-07-18 Hoang-Son Vo , Quang-Vinh Nguyen , Seungwon Kim , Hyung-Jeong Yang , Soonja Yeom , Soo-Hyung Kim

Audio-driven talking head synthesis is a promising topic with wide applications in digital human, film making and virtual reality. Recent NeRF-based approaches have shown superiority in quality and fidelity compared to previous studies.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Dongze Li , Kang Zhao , Wei Wang , Bo Peng , Yingya Zhang , Jing Dong , Tieniu Tan

Video generation has achieved remarkable progress, with generated videos increasingly resembling real ones. However, the rapid advance in generation has outpaced the development of adequate evaluation metrics. Currently, the assessment of…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Nabyl Quignon , Baptiste Chopin , Yaohui Wang , Antitza Dantcheva

Conventional GAN-based models for talking head generation often suffer from limited quality and unstable training. Recent approaches based on diffusion models aimed to address these limitations and improve fidelity. However, they still face…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Seyeon Kim , Siyoon Jin , Jihye Park , Kihong Kim , Jiyoung Kim , Jisu Nam , Seungryong Kim

Audio-driven talking head generation aims to create vivid and realistic videos from a static portrait and speech. Existing AR-based methods rely on intermediate facial representations, which limit their expressiveness and realism.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yuzhe Weng , Haotian Wang , Yuanhong Yu , Jun Du , Shan He , Xiaoyan Wu , Haoran Xu

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 co-speech gesture and talking head generation have been impressive, yet most methods focus on only one of the two tasks. Those that attempt to generate both often rely on separate models or network modules, increasing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-20 Steven Hogue , Chenxu Zhang , Yapeng Tian , Xiaohu Guo

Talking Head Generation (THG), typically driven by audio, is an important and challenging task with broad application prospects in various fields such as digital humans, film production, and virtual reality. While diffusion model-based THG…

Computer Vision and Pattern Recognition · Computer Science 2024-12-02 Weipeng Tan , Chuming Lin , Chengming Xu , Xiaozhong Ji , Junwei Zhu , Chengjie Wang , Yunsheng Wu , Yanwei Fu

Recent advances in audio-driven talking head generation have achieved impressive results in lip synchronization and emotional expression. However, they largely overlook the crucial task of facial attribute editing. This capability is…

Computer Vision and Pattern Recognition · Computer Science 2025-08-28 Guanwen Feng , Zhiyuan Ma , Yunan Li , Jiahao Yang , Junwei Jing , Qiguang Miao

Animating still face images with deep generative models using a speech input signal is an active research topic and has seen important recent progress.However, much of the effort has been put into lip syncing and rendering quality while the…

Graphics · Computer Science 2024-12-13 Louis Airale , Dominique Vaufreydaz , Xavier Alameda-Pineda

Taking inspiration from recent developments in visual generative tasks using diffusion models, we propose a method for end-to-end speech-driven video editing using a denoising diffusion model. Given a video of a talking person, and a…

Computer Vision and Pattern Recognition · Computer Science 2023-05-12 Dan Bigioi , Shubhajit Basak , Michał Stypułkowski , Maciej Zięba , Hugh Jordan , Rachel McDonnell , Peter Corcoran

Talking Head Generation (THG) has emerged as a transformative technology in computer vision, enabling the synthesis of realistic human faces synchronized with image, audio, text, or video inputs. This paper provides a comprehensive review…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Vineet Kumar Rakesh , Soumya Mazumdar , Research Pratim Maity , Sarbajit Pal , Amitabha Das , Tapas Samanta

Audio-driven 3D facial animation aims to generate synchronized lip movements and vivid facial expressions from arbitrary audio clips. While existing methods can produce synchronized lip motions, they often rely on predefined identity or…

Computer Vision and Pattern Recognition · Computer Science 2026-05-29 Xuangeng Chu , Yuan Gan , Ziteng Cui , Shuhong Liu , Jian Wang , Bing Zhou , Tatsuya Harada

Cross-modality generation is an emerging topic that aims to synthesize data in one modality based on information in a different modality. In this paper, we consider a task of such: given an arbitrary audio speech and one lip image of…

Computer Vision and Pattern Recognition · Computer Science 2018-05-23 Lele Chen , Zhiheng Li , Ross K. Maddox , Zhiyao Duan , Chenliang Xu

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

Audio-driven talking head animation is a challenging research topic with many real-world applications. Recent works have focused on creating photo-realistic 2D animation, while learning different talking or singing styles remains an open…

Computer Vision and Pattern Recognition · Computer Science 2023-03-23 Trong-Thang Pham , Nhat Le , Tuong Do , Hung Nguyen , Erman Tjiputra , Quang D. Tran , Anh Nguyen

Speech-driven 3D facial animation plays a key role in applications such as virtual avatars, gaming, and digital content creation. While existing methods have made significant progress in achieving accurate lip synchronization and generating…

Graphics · Computer Science 2025-07-16 Yifang Pan , Karan Singh , Luiz Gustavo Hafemann
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