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High-quality AI-powered video dubbing demands precise audio-lip synchronization, high-fidelity visual generation, and faithful preservation of identity and background. Most existing methods rely on a mask-based training strategy, where the…

Computer Vision and Pattern Recognition · Computer Science 2026-02-09 Xindi Zhang , Dechao Meng , Steven Xiao , Qi Wang , Peng Zhang , Bang Zhang

Cross-modality generation is an emerging topic that aims to synthesize data in one modality based on information in a different modality. In this paper, we consider a task of such: given an arbitrary audio speech and one lip image of…

Computer Vision and Pattern Recognition · Computer Science 2018-05-23 Lele Chen , Zhiheng Li , Ross K. Maddox , Zhiyao Duan , Chenliang Xu

Audio-driven 3D facial animation aims to map input audio to realistic facial motion. Despite significant progress, limitations arise from inconsistent 3D annotations, restricting previous models to training on specific annotations and…

Computer Vision and Pattern Recognition · Computer Science 2024-08-02 Xiangyu Fan , Jiaqi Li , Zhiqian Lin , Weiye Xiao , Lei Yang

Speech-driven talking head generation is a critical yet challenging task with applications in augmented reality and virtual human modeling. While recent approaches using autoregressive and diffusion-based models have achieved notable…

Computer Vision and Pattern Recognition · Computer Science 2025-12-08 Yihong Lin , Zhaoxin Fan , Xianjia Wu , Lingyu Xiong , Liang Peng , Xiandong Li , Wenxiong Kang , Songju Lei , Huang Xu

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

In this paper, we consider a novel and practical case for talking face video generation. Specifically, we focus on the scenarios involving multi-people interactions, where the talking context, such as audience or surroundings, is present.…

Computer Vision and Pattern Recognition · Computer Science 2024-02-29 Meidai Xuanyuan , Yuwang Wang , Honglei Guo , Qionghai Dai

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

Audio-driven single-image talking portrait generation plays a crucial role in virtual reality, digital human creation, and filmmaking. Existing approaches are generally categorized into keypoint-based and image-based methods. Keypoint-based…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Chaolong Yang , Kai Yao , Yuyao Yan , Chenru Jiang , Weiguang Zhao , Jie Sun , Guangliang Cheng , Yifei Zhang , Bin Dong , Kaizhu Huang

Talking head synthesis, an advanced method for generating portrait videos from a still image driven by specific content, has garnered widespread attention in virtual reality, augmented reality and game production. Recently, significant…

Computer Vision and Pattern Recognition · Computer Science 2024-06-19 Ming Meng , Yufei Zhao , Bo Zhang , Yonggui Zhu , Weimin Shi , Maxwell Wen , Zhaoxin Fan

We introduce VASA, a framework for generating lifelike talking faces with appealing visual affective skills (VAS) given a single static image and a speech audio clip. Our premiere model, VASA-1, is capable of not only generating lip…

Computer Vision and Pattern Recognition · Computer Science 2024-11-01 Sicheng Xu , Guojun Chen , Yu-Xiao Guo , Jiaolong Yang , Chong Li , Zhenyu Zang , Yizhong Zhang , Xin Tong , Baining Guo

The rapid advancement of large language models (LLMs) has significantly propelled the development of text-based chatbots, demonstrating their capability to engage in coherent and contextually relevant dialogues. However, extending these…

Computation and Language · Computer Science 2024-08-23 Yinghao Aaron Li , Xilin Jiang , Jordan Darefsky , Ge Zhu , Nima Mesgarani

Speech-driven facial animation methods usually contain two main classes, 3D and 2D talking face, both of which attract considerable research attention in recent years. However, to the best of our knowledge, the research on 3D talking face…

Computer Vision and Pattern Recognition · Computer Science 2024-04-22 Yixiang Zhuang , Baoping Cheng , Yao Cheng , Yuntao Jin , Renshuai Liu , Chengyang Li , Xuan Cheng , Jing Liao , Juncong Lin

Audio-driven talking-head generation is a crucial and useful technology for virtual human interaction and film-making. While recent advances have focused on improving image fidelity and lip synchronization, generating accurate emotional…

Computer Vision and Pattern Recognition · Computer Science 2025-05-05 Wenqing Wang , Yun Fu

In this paper, we propose a talking face generation method that takes an audio signal as input and a short target video clip as reference, and synthesizes a photo-realistic video of the target face with natural lip motions, head poses, and…

Computer Vision and Pattern Recognition · Computer Science 2021-08-19 Chenxu Zhang , Yifan Zhao , Yifei Huang , Ming Zeng , Saifeng Ni , Madhukar Budagavi , Xiaohu Guo

Conventional GAN-based models for talking head generation often suffer from limited quality and unstable training. Recent approaches based on diffusion models aimed to address these limitations and improve fidelity. However, they still face…

Computer Vision and Pattern Recognition · Computer Science 2024-03-29 Seyeon Kim , Siyoon Jin , Jihye Park , Kihong Kim , Jiyoung Kim , Jisu Nam , Seungryong Kim

Diffusion-based audio-driven talking-head generation enables realistic portrait animation, but also introduces risks of misuse, such as fraud and misinformation. Existing protection methods are largely limited to a single modality, and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-13 Wenli Zhang , Xianglong Shi , Sirui Zhao , Xinqi Chen , Guo Cheng , Yifan Xu , Tong Xu , Yong Liao

Text-to-Speech (TTS) has recently seen great progress in synthesizing high-quality speech owing to the rapid development of parallel TTS systems, but producing speech with naturalistic prosodic variations, speaking styles and emotional…

Audio and Speech Processing · Electrical Eng. & Systems 2023-11-21 Yinghao Aaron Li , Cong Han , Nima Mesgarani

Speech-driven 3D facial animation aims to synthesize vivid facial animations that accurately synchronize with speech and match the unique speaking style. However, existing works primarily focus on achieving precise lip synchronization while…

Computer Vision and Pattern Recognition · Computer Science 2023-12-19 Hui Fu , Zeqing Wang , Ke Gong , Keze Wang , Tianshui Chen , Haojie Li , Haifeng Zeng , Wenxiong Kang

One-shot 3D talking portrait generation aims to reconstruct a 3D avatar from an unseen image, and then animate it with a reference video or audio to generate a talking portrait video. The existing methods fail to simultaneously achieve the…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Zhenhui Ye , Tianyun Zhong , Yi Ren , Jiaqi Yang , Weichuang Li , Jiawei Huang , Ziyue Jiang , Jinzheng He , Rongjie Huang , Jinglin Liu , Chen Zhang , Xiang Yin , Zejun Ma , Zhou Zhao

The task of converting text input into video content is becoming an important topic for synthetic media generation. Several methods have been proposed with some of them reaching close-to-natural performances in constrained tasks. In this…

Audio and Speech Processing · Electrical Eng. & Systems 2022-06-08 Dan Oneata , Beata Lorincz , Adriana Stan , Horia Cucu