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Despite exhibiting impressive performance in synthesizing lifelike personalized 3D talking heads, prevailing methods based on radiance fields suffer from high demands for training data and time for each new identity. This paper introduces…

Computer Vision and Pattern Recognition · Computer Science 2025-02-28 Jiahe Li , Jiawei Zhang , Xiao Bai , Jin Zheng , Jun Zhou , Lin Gu

Speech-driven 3D talking face method should offer both accurate lip synchronization and controllable expressions. Previous methods solely adopt discrete emotion labels to globally control expressions throughout sequences while limiting…

Computer Vision and Pattern Recognition · Computer Science 2025-03-20 Hejia Chen , Haoxian Zhang , Shoulong Zhang , Xiaoqiang Liu , Sisi Zhuang , Yuan Zhang , Pengfei Wan , Di Zhang , Shuai Li

Talking head synthesis, also known as speech-to-lip synthesis, reconstructs the facial motions that align with the given audio tracks. The synthesized videos are evaluated on mainly two aspects, lip-speech synchronization and image…

Machine Learning · Computer Science 2025-03-18 Xulin Fan , Heting Gao , Ziyi Chen , Peng Chang , Mei Han , Mark Hasegawa-Johnson

Talking head generation is to generate video based on a given source identity and target motion. However, current methods face several challenges that limit the quality and controllability of the generated videos. First, the generated face…

Computer Vision and Pattern Recognition · Computer Science 2023-11-03 Yue Gao , Yuan Zhou , Jinglu Wang , Xiao Li , Xiang Ming , Yan Lu

Talking face generation aims to synthesize a sequence of face images that correspond to a clip of speech. This is a challenging task because face appearance variation and semantics of speech are coupled together in the subtle movements of…

Computer Vision and Pattern Recognition · Computer Science 2019-04-24 Hang Zhou , Yu Liu , Ziwei Liu , Ping Luo , Xiaogang 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

Expressions are fundamental to conveying human emotions. With the rapid advancement of AI-generated content (AIGC), realistic and expressive 3D facial animation has become increasingly crucial. Despite recent progress in speech-driven…

Computer Vision and Pattern Recognition · Computer Science 2025-10-30 Yuxiang Mao , Zhijie Zhang , Zhiheng Zhang , Jiawei Liu , Chen Zeng , Shihong Xia

Direct speech-to-speech translation achieves high-quality results through the introduction of discrete units obtained from self-supervised learning. This approach circumvents delays and cascading errors associated with model cascading.…

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

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

This paper introduces Stereo-Talker, a novel one-shot audio-driven human video synthesis system that generates 3D talking videos with precise lip synchronization, expressive body gestures, temporally consistent photo-realistic quality, and…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Xiang Deng , Youxin Pang , Xiaochen Zhao , Chao Xu , Lizhen Wang , Hongjiang Xiao , Shi Yan , Hongwen Zhang , Yebin Liu

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

Individuals have unique facial expression and head pose styles that reflect their personalized speaking styles. Existing one-shot talking head methods cannot capture such personalized characteristics and therefore fail to produce diverse…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Suzhen Wang , Yifeng Ma , Yu Ding , Zhipeng Hu , Changjie Fan , Tangjie Lv , Zhidong Deng , Xin Yu

Diffusion models have revolutionized the field of talking head generation, yet still face challenges in expressiveness, controllability, and stability in long-time generation. In this research, we propose an EmotiveTalk framework to address…

Computer Vision and Pattern Recognition · Computer Science 2024-12-17 Haotian Wang , Yuzhe Weng , Yueyan Li , Zilu Guo , Jun Du , Shutong Niu , Jiefeng Ma , Shan He , Xiaoyan Wu , Qiming Hu , Bing Yin , Cong Liu , Qingfeng Liu

Talking face generation, also known as speech-to-lip generation, reconstructs facial motions concerning lips given coherent speech input. The previous studies revealed the importance of lip-speech synchronization and visual quality. Despite…

Computer Vision and Pattern Recognition · Computer Science 2023-03-31 Jiadong Wang , Xinyuan Qian , Malu Zhang , Robby T. Tan , Haizhou Li

We consider the task of animating 3D facial geometry from speech signal. Existing works are primarily deterministic, focusing on learning a one-to-one mapping from speech signal to 3D face meshes on small datasets with limited speakers.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-01 Karren D. Yang , Anurag Ranjan , Jen-Hao Rick Chang , Raviteja Vemulapalli , Oncel Tuzel

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

In the task of talking face generation, the objective is to generate a face video with lips synchronized to the corresponding audio while preserving visual details and identity information. Current methods face the challenge of learning…

Computer Vision and Pattern Recognition · Computer Science 2024-05-08 Dogucan Yaman , Fevziye Irem Eyiokur , Leonard Bärmann , Seymanur Aktı , Hazım Kemal Ekenel , Alexander Waibel

Researchers have shown a growing interest in Audio-driven Talking Head Generation. The primary challenge in talking head generation is achieving audio-visual coherence between the lips and the audio, known as lip synchronization. This paper…

Sound · Computer Science 2026-02-03 Zhipeng Chen , Xinheng Wang , Lun Xie , Haijie Yuan , Hang Pan

Audio-driven talking head generation is advancing from 2D to 3D content. Notably, Neural Radiance Field (NeRF) is in the spotlight as a means to synthesize high-quality 3D talking head outputs. Unfortunately, this NeRF-based approach…

Computer Vision and Pattern Recognition · Computer Science 2024-05-13 Gihoon Kim , Kwanggyoon Seo , Sihun Cha , Junyong Noh
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