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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

Despite recent advances in syncing lip movements with any audio waves, current methods still struggle to balance generation quality and the model's generalization ability. Previous studies either require long-term data for training or…

Computer Vision and Pattern Recognition · Computer Science 2023-05-10 Jiazhi Guan , Zhanwang Zhang , Hang Zhou , Tianshu Hu , Kaisiyuan Wang , Dongliang He , Haocheng Feng , Jingtuo Liu , Errui Ding , Ziwei Liu , Jingdong Wang

Current audio-driven 3D head generation methods mainly focus on single-speaker scenarios, lacking natural, bidirectional listen-and-speak interaction. Achieving seamless conversational behavior, where speaking and listening states…

Computer Vision and Pattern Recognition · Computer Science 2026-01-06 Lei Zhu , Lijian Lin , Ye Zhu , Jiahao Wu , Xuehan Hou , Yu Li , Yunfei Liu , Jie Chen

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

This paper presents a generic method for generating full facial 3D animation from speech. Existing approaches to audio-driven facial animation exhibit uncanny or static upper face animation, fail to produce accurate and plausible…

Computer Vision and Pattern Recognition · Computer Science 2022-05-23 Alexander Richard , Michael Zollhoefer , Yandong Wen , Fernando de la Torre , Yaser Sheikh

Although existing speech-driven talking face generation methods achieve significant progress, they are far from real-world application due to the avatar-specific training demand and unstable lip movements. To address the above issues, we…

Computer Vision and Pattern Recognition · Computer Science 2023-12-13 Haiming Zhang , Zhihao Yuan , Chaoda Zheng , Xu Yan , Baoyuan Wang , Guanbin Li , Song Wu , Shuguang Cui , Zhen Li

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

While state-of-the-art audio-video generation models like Veo3 and Sora2 demonstrate remarkable capabilities, their closed-source nature makes their architectures and training paradigms inaccessible. To bridge this gap in accessibility and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-03 Hebeizi Li , Zihao Liang , Benyuan Sun , Zihao Yin , Xiao Sha , Chenliang Wang , Yi Yang

Diffusion-based talking head generation has achieved remarkable visual quality, yet scaling it to long-term videos remains challenging. The widely adopted chunk-wise paradigm introduces two fundamental failures: (1) temporal-spatial…

Machine Learning · Computer Science 2026-05-12 Yuxin Lu , Jiayang Sun , Guibo Zhu , Min Cao

In this study, we propose a method for video face reenactment that integrates a 3D face parametric model into a latent diffusion framework, aiming to improve shape consistency and motion control in existing video-based face generation…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Mengting Wei , Yante Li , Tuomas Varanka , Yan Jiang , Guoying Zhao

In this paper, we propose a novel audio-driven talking head method capable of simultaneously generating highly expressive facial expressions and hand gestures. Unlike existing methods that focus on generating full-body or half-body poses,…

Computer Vision and Pattern Recognition · Computer Science 2025-01-22 Linrui Tian , Siqi Hu , Qi Wang , Bang Zhang , Liefeng Bo

We present a novel one-shot talking head synthesis method that achieves disentangled and fine-grained control over lip motion, eye gaze&blink, head pose, and emotional expression. We represent different motions via disentangled latent…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Duomin Wang , Yu Deng , Zixin Yin , Heung-Yeung Shum , Baoyuan Wang

Face inpainting techniques recover missing or occluded facial regions in a visually realistic manner, but preserving the identity in the final output remains a fundamental challenge. Identity consistency is crucial for downstream…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 João Santos , Carlos Santiago , Manuel Marques

For audio-driven visual dubbing, it remains a considerable challenge to uphold and highlight speaker's persona while synthesizing accurate lip synchronization. Existing methods fall short of capturing speaker's unique speaking style or…

Computer Vision and Pattern Recognition · Computer Science 2024-09-10 Longhao Zhang , Shuang Liang , Zhipeng Ge , Tianshu Hu

Recently, multi-person video generation has started to gain prominence. While a few preliminary works have explored audio-driven multi-person talking video generation, they often face challenges due to the high costs of diverse multi-person…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Zhizhou Zhong , Yicheng Ji , Zhe Kong , Yiying Liu , Jiarui Wang , Jiasun Feng , Lupeng Liu , Xiangyi Wang , Yanjia Li , Yuqing She , Ying Qin , Huan Li , Shuiyang Mao , Wei Liu , Wenhan Luo

Video editing-based talking face generation aims to preserve video details such as pose, lighting, and gestures while modifying only lip motion, often using an identity reference image to maintain speaker consistency. However, this…

Computer Vision and Pattern Recognition · Computer Science 2026-02-11 Dogucan Yaman , Fevziye Irem Eyiokur , Hazım Kemal Ekenel , Alexander Waibel

Generative models have advanced rapidly, enabling impressive talking head generation that brings AI to life. However, most existing methods focus solely on one-way portrait animation. Even the few that support bidirectional conversational…

Audio and Speech Processing · Electrical Eng. & Systems 2025-11-25 Haijie Yang , Zhenyu Zhang , Hao Tang , Jianjun Qian , Jian Yang

Recently audio-driven talking face video generation has attracted considerable attention. However, very few researches address the issue of emotional editing of these talking face videos with continuously controllable expressions, which is…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zhiyao Sun , Yu-Hui Wen , Tian Lv , Yanan Sun , Ziyang Zhang , Yaoyuan Wang , Yong-Jin Liu

Speech-driven 3D talking head generation aims to produce lifelike facial animations precisely synchronized with speech. While considerable progress has been made in achieving high lip-synchronization accuracy, existing methods largely…

Computer Vision and Pattern Recognition · Computer Science 2025-12-30 Bin Wang , Yang Xu , Huan Zhao , Hao Zhang , Zixing Zhang

Speech-driven 3D facial animation aims to synthesize vivid facial animations that accurately synchronize with speech and match the unique speaking style. However, existing works primarily focus on achieving precise lip synchronization while…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Hui Fu , Zeqing Wang , Ke Gong , Keze Wang , Tianshui Chen , Haojie Li , Haifeng Zeng , Wenxiong Kang
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