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Talking head generation is to synthesize a lip-synchronized talking head video by inputting an arbitrary face image and corresponding audio clips. Existing methods ignore not only the interaction and relationship of cross-modal information,…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Sen Chen , Zhilei Liu , Jiaxing Liu , Longbiao Wang

We propose an audio-driven talking-head method to generate photo-realistic talking-head videos from a single reference image. In this work, we tackle two key challenges: (i) producing natural head motions that match speech prosody, and (ii)…

Computer Vision and Pattern Recognition · Computer Science 2021-07-21 Suzhen Wang , Lincheng Li , Yu Ding , Changjie Fan , Xin Yu

The ability to envisage the visual of a talking face based just on hearing a voice is a unique human capability. There have been a number of works that have solved for this ability recently. We differ from these approaches by enabling a…

Computer Vision and Pattern Recognition · Computer Science 2020-11-24 Ravindra Yadav , Ashish Sardana , Vinay P Namboodiri , Rajesh M Hegde

Talking face generation has historically struggled to produce head movements and natural facial expressions without guidance from additional reference videos. Recent developments in diffusion-based generative models allow for more realistic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-01 Michał Stypułkowski , Konstantinos Vougioukas , Sen He , Maciej Zięba , Stavros Petridis , Maja Pantic

Talking head synthesis is a promising approach for the video production industry. Recently, a lot of effort has been devoted in this research area to improve the generation quality or enhance the model generalization. However, there are few…

Computer Vision and Pattern Recognition · Computer Science 2023-04-21 Shuai Shen , Wenliang Zhao , Zibin Meng , Wanhua Li , Zheng Zhu , Jie Zhou , Jiwen Lu

Audio-driven talking head generation has drawn much attention in recent years, and many efforts have been made in lip-sync, expressive facial expressions, natural head pose generation, and high video quality. However, no model has yet led…

Computer Vision and Pattern Recognition · Computer Science 2023-12-08 Xusen Sun , Longhao Zhang , Hao Zhu , Peng Zhang , Bang Zhang , Xinya Ji , Kangneng Zhou , Daiheng Gao , Liefeng Bo , Xun Cao

The task of talking head generation is to synthesize a lip synchronized talking head video by inputting an arbitrary face image and audio clips. Most existing methods ignore the local driving information of the mouth muscles. In this paper,…

Computer Vision and Pattern Recognition · Computer Science 2021-10-20 Sen Chen , Zhilei Liu , Jiaxing Liu , Zhengxiang Yan , Longbiao Wang

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

Audio-driven talking face generation, which aims to synthesize talking faces with realistic facial animations (including accurate lip movements, vivid facial expression details and natural head poses) corresponding to the audio, has…

Computer Vision and Pattern Recognition · Computer Science 2023-04-19 Rongliang Wu , Yingchen Yu , Fangneng Zhan , Jiahui Zhang , Xiaoqin Zhang , Shijian Lu

Audio-driven talking head generation is a significant and challenging task applicable to various fields such as virtual avatars, film production, and online conferences. However, the existing GAN-based models emphasize generating…

Computer Vision and Pattern Recognition · Computer Science 2024-08-06 Jintao Tan , Xize Cheng , Lingyu Xiong , Lei Zhu , Xiandong Li , Xianjia Wu , Kai Gong , Minglei Li , Yi Cai

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

While accurate lip synchronization has been achieved for arbitrary-subject audio-driven talking face generation, the problem of how to efficiently drive the head pose remains. Previous methods rely on pre-estimated structural information…

Computer Vision and Pattern Recognition · Computer Science 2021-04-23 Hang Zhou , Yasheng Sun , Wayne Wu , Chen Change Loy , Xiaogang Wang , Ziwei Liu

Talking face generation aims to synthesize a face video with precise lip synchronization as well as a smooth transition of facial motion over the entire video via the given speech clip and facial image. Most existing methods mainly focus on…

Computer Vision and Pattern Recognition · Computer Science 2020-05-14 Hao Zhu , Huaibo Huang , Yi Li , Aihua Zheng , Ran He

Audio-driven talking face generation is a challenging task in digital communication. Despite significant progress in the area, most existing methods concentrate on audio-lip synchronization, often overlooking aspects such as visual quality,…

Computer Vision and Pattern Recognition · Computer Science 2025-10-02 Fatemeh Nazarieh , Zhenhua Feng , Diptesh Kanojia , Muhammad Awais , Josef Kittler

Creating a realistic animatable avatar from a single static portrait remains challenging. Existing approaches often struggle to capture subtle facial expressions, the associated global body movements, and the dynamic background. To address…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Mengchao Wang , Qiang Wang , Fan Jiang , Yaqi Fan , Yunpeng Zhang , Yonggang Qi , Kun Zhao , Mu Xu

We propose a two-stage framework for audio-driven talking head generation with fine-grained expression control via facial Action Units (AUs). Unlike prior methods relying on emotion labels or implicit AU conditioning, our model explicitly…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Shao-Yu Chang , Jingyi Xu , Hieu Le , Dimitris Samaras

Recent methods for audio-driven talking head synthesis often optimize neural radiance fields (NeRF) on a monocular talking portrait video, leveraging its capability to render high-fidelity and 3D-consistent novel-view frames. However, they…

Computer Vision and Pattern Recognition · Computer Science 2024-04-01 Jaehoon Ko , Kyusun Cho , Joungbin Lee , Heeji Yoon , Sangmin Lee , Sangjun Ahn , Seungryong Kim

We propose StyleTalker, a novel audio-driven talking head generation model that can synthesize a video of a talking person from a single reference image with accurately audio-synced lip shapes, realistic head poses, and eye blinks.…

Computer Vision and Pattern Recognition · Computer Science 2024-03-18 Dongchan Min , Minyoung Song , Eunji Ko , Sung Ju Hwang

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

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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