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Related papers: EmoVOCA: Speech-Driven Emotional 3D Talking Heads

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The creation of lifelike speech-driven 3D facial animation requires a natural and precise synchronization between audio input and facial expressions. However, existing works still fail to render shapes with flexible head poses and natural…

Computer Vision and Pattern Recognition · Computer Science 2023-11-01 Wei Zhao , Yijun Wang , Tianyu He , Lianying Yin , Jianxin Lin , Xin Jin

Audio-driven talking-head generation has advanced rapidly with diffusion-based generative models, yet producing temporally coherent videos with fine-grained motion control remains challenging. We propose DEMO, a flow-matching generative…

Computer Vision and Pattern Recognition · Computer Science 2025-10-14 Peiyin Chen , Zhuowei Yang , Hui Feng , Sheng Jiang , Rui Yan

Although previous co-speech gesture generation methods are able to synthesize motions in line with speech content, it is still not enough to handle diverse and complicated motion distribution. The key challenges are: 1) the one-to-many…

Computer Vision and Pattern Recognition · Computer Science 2023-06-21 Lianying Yin , Yijun Wang , Tianyu He , Jinming Liu , Wei Zhao , Bohan Li , Xin Jin , Jianxin Lin

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

Audio-driven talking head synthesis has achieved remarkable photorealism, yet state-of-the-art (SOTA) models exhibit a critical failure: they lack generalization to the full spectrum of human diversity in ethnicity, language, and age…

Computer Vision and Pattern Recognition · Computer Science 2025-08-20 Shunian Chen , Hejin Huang , Yexin Liu , Zihan Ye , Pengcheng Chen , Chenghao Zhu , Michael Guan , Rongsheng Wang , Junying Chen , Guanbin Li , Ser-Nam Lim , Harry Yang , Benyou Wang

Although significant progress has been made to audio-driven talking face generation, existing methods either neglect facial emotion or cannot be applied to arbitrary subjects. In this paper, we propose the Emotion-Aware Motion Model (EAMM)…

Computer Vision and Pattern Recognition · Computer Science 2022-09-26 Xinya Ji , Hang Zhou , Kaisiyuan Wang , Qianyi Wu , Wayne Wu , Feng Xu , Xun Cao

Given a piece of text, a video clip, and a reference audio, the movie dubbing task aims to generate speech that aligns with the video while cloning the desired voice. The existing methods have two primary deficiencies: (1) They struggle to…

Speech-driven 3D facial animation has improved a lot recently while most related works only utilize acoustic modality and neglect the influence of visual and textual cues, leading to unsatisfactory results in terms of precision and…

Computer Vision and Pattern Recognition · Computer Science 2023-12-06 Tianshun Han , Shengnan Gui , Yiqing Huang , Baihui Li , Lijian Liu , Benjia Zhou , Ning Jiang , Quan Lu , Ruicong Zhi , Yanyan Liang , Du Zhang , Jun Wan

Recent advancements in speech-driven 3D talking head generation have made significant progress in lip synchronization. However, existing models still struggle to capture the perceptual alignment between varying speech characteristics and…

Graphics · Computer Science 2025-04-01 Lee Chae-Yeon , Oh Hyun-Bin , Han EunGi , Kim Sung-Bin , Suekyeong Nam , Tae-Hyun Oh

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

Recent advances in Talking Head Generation (THG) have achieved impressive lip synchronization and visual quality through diffusion models; yet existing methods struggle to generate emotionally expressive portraits while preserving speaker…

Computer Vision and Pattern Recognition · Computer Science 2025-08-07 Weipeng Tan , Chuming Lin , Chengming Xu , FeiFan Xu , Xiaobin Hu , Xiaozhong Ji , Junwei Zhu , Chengjie Wang , Yanwei Fu

We propose emotion2vec, a universal speech emotion representation model. emotion2vec is pre-trained on open-source unlabeled emotion data through self-supervised online distillation, combining utterance-level loss and frame-level loss…

Computation and Language · Computer Science 2023-12-27 Ziyang Ma , Zhisheng Zheng , Jiaxin Ye , Jinchao Li , Zhifu Gao , Shiliang Zhang , Xie Chen

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

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

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

Audio-driven talking face generation has received growing interest, particularly for applications requiring expressive and natural human-avatar interaction. However, most existing emotion-aware methods rely on a single modality (either…

Computer Vision and Pattern Recognition · Computer Science 2025-09-25 Phyo Thet Yee , Dimitrios Kollias , Sudeepta Mishra , Abhinav Dhall

Whenever we speak, our voice is accompanied by facial movements and expressions. Several recent works have shown the synthesis of highly photo-realistic videos of talking faces, but they either require a source video to drive the target…

Computer Vision and Pattern Recognition · Computer Science 2020-11-03 Prateek Manocha , Prithwijit Guha

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

We propose DiffSHEG, a Diffusion-based approach for Speech-driven Holistic 3D Expression and Gesture generation with arbitrary length. While previous works focused on co-speech gesture or expression generation individually, the joint…

Sound · Computer Science 2024-04-09 Junming Chen , Yunfei Liu , Jianan Wang , Ailing Zeng , Yu Li , Qifeng Chen

Head avatars animated by visual signals have gained popularity, particularly in cross-driving synthesis where the driver differs from the animated character, a challenging but highly practical approach. The recently presented MegaPortraits…

Computer Vision and Pattern Recognition · Computer Science 2024-05-01 Nikita Drobyshev , Antoni Bigata Casademunt , Konstantinos Vougioukas , Zoe Landgraf , Stavros Petridis , Maja Pantic
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