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Recent advancements in audio-driven talking face generation have made great progress in lip synchronization. However, current methods often lack sufficient control over facial animation such as speaking style and emotional expression,…

Computer Vision and Pattern Recognition · Computer Science 2025-03-21 Baiqin Wang , Xiangyu Zhu , Fan Shen , Hao Xu , Zhen Lei

Audio-driven talking-head generation is a crucial and useful technology for virtual human interaction and film-making. While recent advances have focused on improving image fidelity and lip synchronization, generating accurate emotional…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Wenqing Wang , Yun Fu

Generating realistic human motions that naturally respond to both spoken language and physical objects is crucial for interactive digital experiences. Current methods, however, address speech-driven gestures or object interactions…

Computer Vision and Pattern Recognition · Computer Science 2025-12-16 Sreehari Rajan , Kunal Bhosikar , Charu Sharma

Audio-driven talking head generation has drawn growing attention. To produce talking head videos with desired facial expressions, previous methods rely on extra reference videos to provide expression information, which may be difficult to…

Computer Vision and Pattern Recognition · Computer Science 2024-08-13 Yifeng Ma , Suzhen Wang , Yu Ding , Bowen Ma , Tangjie Lv , Changjie Fan , Zhipeng Hu , Zhidong Deng , Xin Yu

When people deliver a speech, they naturally move heads, and this rhythmic head motion conveys prosodic information. However, generating a lip-synced video while moving head naturally is challenging. While remarkably successful, existing…

Computer Vision and Pattern Recognition · Computer Science 2020-07-20 Lele Chen , Guofeng Cui , Celong Liu , Zhong Li , Ziyi Kou , Yi Xu , Chenliang Xu

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

In human-centric content generation, the pre-trained text-to-image models struggle to produce user-wanted portrait images, which retain the identity of individuals while exhibiting diverse expressions. This paper introduces our efforts…

Computer Vision and Pattern Recognition · Computer Science 2024-04-09 Renshuai Liu , Bowen Ma , Wei Zhang , Zhipeng Hu , Changjie Fan , Tangjie Lv , Yu Ding , Xuan Cheng

This paper addresses the problem of generating lifelike holistic co-speech motions for 3D avatars, focusing on two key aspects: variability and coordination. Variability allows the avatar to exhibit a wide range of motions even with similar…

Computer Vision and Pattern Recognition · Computer Science 2024-04-16 Yifei Liu , Qiong Cao , Yandong Wen , Huaiguang Jiang , Changxing Ding

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

For realistic talking head generation, creating natural head motion while maintaining accurate lip synchronization is essential. To fulfill this challenging task, we propose DisCoHead, a novel method to disentangle and control head pose and…

Computer Vision and Pattern Recognition · Computer Science 2023-03-15 Geumbyeol Hwang , Sunwon Hong , Seunghyun Lee , Sungwoo Park , Gyeongsu Chae

We propose X-Portrait, an innovative conditional diffusion model tailored for generating expressive and temporally coherent portrait animation. Specifically, given a single portrait as appearance reference, we aim to animate it with motion…

Computer Vision and Pattern Recognition · Computer Science 2024-07-29 You Xie , Hongyi Xu , Guoxian Song , Chao Wang , Yichun Shi , Linjie Luo

Speech-driven 3D facial animation technology has been developed for years, but its practical application still lacks expectations. The main challenges lie in data limitations, lip alignment, and the naturalness of facial expressions.…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiangyu Liang , Wenlin Zhuang , Tianyong Wang , Guangxing Geng , Guangyue Geng , Haifeng Xia , Siyu Xia

In this paper, we present FaceShot, a novel training-free portrait animation framework designed to bring any character into life from any driven video without fine-tuning or retraining. We achieve this by offering precise and robust reposed…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Junyao Gao , Yanan Sun , Fei Shen , Xin Jiang , Zhening Xing , Kai Chen , Cairong Zhao

Controllability, generalizability and efficiency are the major objectives of constructing face avatars represented by neural implicit field. However, existing methods have not managed to accommodate the three requirements simultaneously.…

Computer Vision and Pattern Recognition · Computer Science 2023-03-28 Zhiyuan Ma , Xiangyu Zhu , Guojun Qi , Zhen Lei , Lei Zhang

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

Audio-driven facial animation is essential for immersive digital interaction, yet existing frameworks fail to reconcile real-time streaming with high-fidelity personalization. Current methods often rely on latency-inducing audio look-ahead,…

Graphics · Computer Science 2026-04-28 Xuangeng Chu , Yu Han , Wei Mao , Shih-En Wei

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

One-shot talking head video generation uses a source image and driving video to create a synthetic video where the source person's facial movements imitate those of the driving video. However, differences in scale between the source and…

Computer Vision and Pattern Recognition · Computer Science 2024-07-16 Fa-Ting Hong , Dan Xu

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

We aim to edit the lip movements in talking video according to the given speech while preserving the personal identity and visual details. The task can be decomposed into two sub-problems: (1) speech-driven lip motion generation and (2)…

Computer Vision and Pattern Recognition · Computer Science 2024-06-18 Runyi Yu , Tianyu He , Ailing Zhang , Yuchi Wang , Junliang Guo , Xu Tan , Chang Liu , Jie Chen , Jiang Bian
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