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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 head synthesis is to synthesize a lip-synchronized talking head video using audio. Recently, the capability of NeRF to enhance the realism and texture details of synthesized talking heads has attracted the attention of researchers.…

Graphics · Computer Science 2025-02-21 Xiaoxing Liu , Zhilei Liu , Chongke Bi

Talking head synthesis is a practical technique with wide applications. Current Neural Radiance Field (NeRF) based approaches have shown their superiority on driving one-shot talking heads with videos or signals regressed from audio.…

Computer Vision and Pattern Recognition · Computer Science 2024-08-20 Dongze Li , Kang Zhao , Wei Wang , Yifeng Ma , Bo Peng , Yingya Zhang , Jing Dong

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

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

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

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

Generating high-fidelity talking head video by fitting with the input audio sequence is a challenging problem that receives considerable attentions recently. In this paper, we address this problem with the aid of neural scene representation…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Yudong Guo , Keyu Chen , Sen Liang , Yong-Jin Liu , Hujun Bao , Juyong Zhang

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

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

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

Generating talking avatar driven by audio remains a significant challenge. Existing methods typically require high computational costs and often lack sufficient facial detail and realism, making them unsuitable for applications that demand…

Computer Vision and Pattern Recognition · Computer Science 2025-01-27 Yujian Liu , Shidang Xu , Jing Guo , Dingbin Wang , Zairan Wang , Xianfeng Tan , Xiaoli Liu

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

We introduce a novel method for joint expression and audio-guided talking face generation. Recent approaches either struggle to preserve the speaker identity or fail to produce faithful facial expressions. To address these challenges, we…

Computer Vision and Pattern Recognition · Computer Science 2024-09-19 Sai Tanmay Reddy Chakkera , Aggelina Chatziagapi , Dimitris Samaras

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

High-fidelity facial avatar reconstruction from a monocular video is a significant research problem in computer graphics and computer vision. Recently, Neural Radiance Field (NeRF) has shown impressive novel view rendering results and has…

Computer Vision and Pattern Recognition · Computer Science 2023-03-07 Yunpeng Bai , Yanbo Fan , Xuan Wang , Yong Zhang , Jingxiang Sun , Chun Yuan , Ying Shan

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

Dynamic Neural Radiance Fields (NeRF) have demonstrated considerable success in generating high-fidelity 3D models of talking portraits. Despite significant advancements in the rendering speed and generation quality, challenges persist in…

Computer Vision and Pattern Recognition · Computer Science 2026-01-28 Yuhui Zhang , Hui Yu , Wei Liang , Sunjie Zhang

Animating high-fidelity video portrait with speech audio is crucial for virtual reality and digital entertainment. While most previous studies rely on accurate explicit structural information, recent works explore the implicit scene…

Computer Vision and Pattern Recognition · Computer Science 2022-02-11 Xian Liu , Yinghao Xu , Qianyi Wu , Hang Zhou , Wayne Wu , Bolei Zhou
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