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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

Generating photo-realistic video portrait with arbitrary speech audio is a crucial problem in film-making and virtual reality. Recently, several works explore the usage of neural radiance field in this task to improve 3D realness and image…

Computer Vision and Pattern Recognition · Computer Science 2023-02-01 Zhenhui Ye , Ziyue Jiang , Yi Ren , Jinglin Liu , JinZheng He , Zhou Zhao

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

Talking face synthesis driven by audio is one of the current research hotspots in the fields of multidimensional signal processing and multimedia. Neural Radiance Field (NeRF) has recently been brought to this research field in order to…

Computer Vision and Pattern Recognition · Computer Science 2024-05-17 Chongke Bi , Xiaoxing Liu , Zhilei Liu

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

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

Generating talking person portraits with arbitrary speech audio is a crucial problem in the field of digital human and metaverse. A modern talking face generation method is expected to achieve the goals of generalized audio-lip…

Computer Vision and Pattern Recognition · Computer Science 2023-05-02 Zhenhui Ye , Jinzheng He , Ziyue Jiang , Rongjie Huang , Jiawei Huang , Jinglin Liu , Yi Ren , Xiang Yin , Zejun Ma , Zhou Zhao

While recent advances in deep neural networks have made it possible to render high-quality images, generating photo-realistic and personalized talking head remains challenging. With given audio, the key to tackling this task is…

Computer Vision and Pattern Recognition · Computer Science 2022-01-04 Shunyu Yao , RuiZhe Zhong , Yichao Yan , Guangtao Zhai , Xiaokang Yang

All previous methods for audio-driven talking head generation assume the input audio to be clean with a neutral tone. As we show empirically, one can easily break these systems by simply adding certain background noise to the utterance or…

Computer Vision and Pattern Recognition · Computer Science 2019-10-03 Gaurav Mittal , Baoyuan Wang

The talking head generation recently attracted considerable attention due to its widespread application prospects, especially for digital avatars and 3D animation design. Inspired by this practical demand, several works explored Neural…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Tianyong Wang , Xiangyu Liang , Wangguandong Zheng , Dan Niu , Haifeng Xia , Siyu Xia

While dynamic Neural Radiance Fields (NeRF) have shown success in high-fidelity 3D modeling of talking portraits, the slow training and inference speed severely obstruct their potential usage. In this paper, we propose an efficient…

Computer Vision and Pattern Recognition · Computer Science 2022-11-23 Jiaxiang Tang , Kaisiyuan Wang , Hang Zhou , Xiaokang Chen , Dongliang He , Tianshu Hu , Jingtuo Liu , Gang Zeng , Jingdong Wang

Audio-driven talking head synthesis is a promising topic with wide applications in digital human, film making and virtual reality. Recent NeRF-based approaches have shown superiority in quality and fidelity compared to previous studies.…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Dongze Li , Kang Zhao , Wei Wang , Bo Peng , Yingya Zhang , Jing Dong , Tieniu Tan

Representations used for Facial Expression Recognition (FER) usually contain expression information along with identity features. In this paper, we propose a novel Disentangled Expression learning-Generative Adversarial Network (DE-GAN)…

Computer Vision and Pattern Recognition · Computer Science 2019-12-04 Kamran Ali , Charles E. Hughes

Conversation is an essential component of virtual avatar activities in the metaverse. With the development of natural language processing, textual and vocal conversation generation has achieved a significant breakthrough. However,…

Computer Vision and Pattern Recognition · Computer Science 2023-08-15 Yichao Yan , Zanwei Zhou , Zi Wang , Jingnan Gao , Xiaokang Yang

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

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

Significant progress has been made in talking-face video generation research; however, precise lip-audio synchronization and high visual quality remain challenging in editing lip shapes based on input audio. This paper introduces JoyGen, a…

Computer Vision and Pattern Recognition · Computer Science 2025-01-06 Qili Wang , Dajiang Wu , Zihang Xu , Junshi Huang , Jun Lv

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

Audio-driven talking face generation has garnered significant interest within the domain of digital human research. Existing methods are encumbered by intricate model architectures that are intricately dependent on each other, complicating…

Computer Vision and Pattern Recognition · Computer Science 2024-11-08 Dong Zhao , Jiaying Shi , Wenjun Li , Shudong Wang , Shenghui Xu , Zhaoming Pan

Given an arbitrary face image and an arbitrary speech clip, the proposed work attempts to generating the talking face video with accurate lip synchronization while maintaining smooth transition of both lip and facial movement over the…

Computer Vision and Pattern Recognition · Computer Science 2019-07-29 Yang Song , Jingwen Zhu , Dawei Li , Xiaolong Wang , Hairong Qi
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