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Related papers: AUHead: Realistic Emotional Talking Head Generatio…

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Recent talking avatar generation models have made strides in achieving realistic and accurate lip synchronization with the audio, but often fall short in controlling and conveying detailed expressions and emotions of the avatar, making the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Yuchi Wang , Junliang Guo , Jianhong Bai , Runyi Yu , Tianyu He , Xu Tan , Xu Sun , Jiang Bian

Real-world talking faces often accompany with natural head movement. However, most existing talking face video generation methods only consider facial animation with fixed head pose. In this paper, we address this problem by proposing a…

Computer Vision and Pattern Recognition · Computer Science 2020-03-06 Ran Yi , Zipeng Ye , Juyong Zhang , Hujun Bao , Yong-Jin Liu

Laughter is a unique expression, essential to affirmative social interactions of humans. Although current 3D talking head generation methods produce convincing verbal articulations, they often fail to capture the vitality and subtleties of…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Kim Sung-Bin , Lee Hyun , Da Hye Hong , Suekyeong Nam , Janghoon Ju , Tae-Hyun Oh

Diffusion-based video generation techniques have significantly improved zero-shot talking-head avatar generation, enhancing the naturalness of both head motion and facial expressions. However, existing methods suffer from poor…

Graphics · Computer Science 2025-04-24 Lingzhou Mu , Baiji Liu , Ruonan Zhang , Guiming Mo , Jiawei Jin , Kai Zhang , Haozhi Huang

This work proposes a novel method to generate realistic talking head videos using audio and visual streams. We animate a source image by transferring head motion from a driving video using a dense motion field generated using learnable…

Computer Vision and Pattern Recognition · Computer Science 2022-10-07 Madhav Agarwal , Rudrabha Mukhopadhyay , Vinay Namboodiri , C V Jawahar

Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of truly interactive communication, often generating one-way…

Machine Learning · Computer Science 2026-01-05 Taekyung Ki , Sangwon Jang , Jaehyeong Jo , Jaehong Yoon , Sung Ju Hwang

Person-generic audio-driven face generation is a challenging task in computer vision. Previous methods have achieved remarkable progress in audio-visual synchronization, but there is still a significant gap between current results and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Xiaozhong Ji , Chuming Lin , Zhonggan Ding , Ying Tai , Junwei Zhu , Xiaobin Hu , Donghao Luo , Yanhao Ge , Chengjie Wang

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

In this paper, we introduce a simple and novel framework for one-shot audio-driven talking head generation. Unlike prior works that require additional driving sources for controlled synthesis in a deterministic manner, we instead…

Graphics · Computer Science 2022-12-09 Zhentao Yu , Zixin Yin , Deyu Zhou , Duomin Wang , Finn Wong , Baoyuan Wang

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

Audio-driven human video generation has achieved remarkable success in monologue scenarios, largely driven by advancements in powerful video generation foundation models. Moving beyond monologues, authentic human communication is inherently…

Artificial Intelligence · Computer Science 2026-04-14 Yuzhe Weng , Haotian Wang , Xinyi Yu , Xiaoyan Wu , Haoran Xu , Shan He , Jun Du

Emotionally talking head video generation aims to generate expressive portrait videos with accurate lip synchronization and emotional facial expressions. Current methods rely on simple emotional labels, leading to insufficient semantic…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Yahui Li , Yinfeng Yu , Liejun Wang , Shengjie Shen

Full-stack multimodal interaction in real-time is a central goal in building intelligent embodied agents capable of natural, dynamic communication. However, existing systems are either limited to unimodal generation or suffer from degraded…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xiang Deng , Feng Gao , Yong Zhang , Youxin Pang , Xu Xiaoming , Zhuoliang Kang , Xiaoming Wei , Yebin Liu

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

Vivid talking face generation holds immense potential applications across diverse multimedia domains, such as film and game production. While existing methods accurately synchronize lip movements with input audio, they typically ignore…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Jiadong Liang , Feng Lu

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

In this work, we tackle the challenge of enhancing the realism and expressiveness in talking head video generation by focusing on the dynamic and nuanced relationship between audio cues and facial movements. We identify the limitations of…

Computer Vision and Pattern Recognition · Computer Science 2024-08-09 Linrui Tian , Qi Wang , Bang Zhang , Liefeng Bo

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

This paper investigates a novel task of talking face video generation solely from speeches. The speech-to-video generation technique can spark interesting applications in entertainment, customer service, and human-computer-interaction…

Sound · Computer Science 2021-07-15 Shijing Si , Jianzong Wang , Xiaoyang Qu , Ning Cheng , Wenqi Wei , Xinghua Zhu , Jing Xiao

Recent advances in video diffusion models have unlocked new potential for realistic audio-driven talking video generation. However, achieving seamless audio-lip synchronization, maintaining long-term identity consistency, and producing…

Computer Vision and Pattern Recognition · Computer Science 2024-12-06 Longtao Zheng , Yifan Zhang , Hanzhong Guo , Jiachun Pan , Zhenxiong Tan , Jiahao Lu , Chuanxin Tang , Bo An , Shuicheng Yan