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Audio-driven one-shot talking face generation methods are usually trained on video resources of various persons. However, their created videos often suffer unnatural mouth shapes and asynchronous lips because those methods struggle to learn…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Suzhen Wang , Lincheng Li , Yu Ding , Xin Yu

Recently audio-driven talking face video generation has attracted considerable attention. However, very few researches address the issue of emotional editing of these talking face videos with continuously controllable expressions, which is…

Computer Vision and Pattern Recognition · Computer Science 2023-11-29 Zhiyao Sun , Yu-Hui Wen , Tian Lv , Yanan Sun , Ziyang Zhang , Yaoyuan Wang , Yong-Jin Liu

Although automatically animating audio-driven talking heads has recently received growing interest, previous efforts have mainly concentrated on achieving lip synchronization with the audio, neglecting two crucial elements for generating…

Computer Vision and Pattern Recognition · Computer Science 2024-03-13 Shuai Tan , Bin Ji , Ye Pan

Talking face generation is a novel and challenging generation task, aiming at synthesizing a vivid speaking-face video given a specific audio. To fulfill emotion-controllable talking face generation, current methods need to overcome two…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Ziqi Zhang , Cheng Deng

We present a novel approach for synthesizing 3D facial motions from audio sequences using key motion embeddings. Despite recent advancements in data-driven techniques, accurately mapping between audio signals and 3D facial meshes remains…

Computer Vision and Pattern Recognition · Computer Science 2024-09-04 Zhihao Xu , Shengjie Gong , Jiapeng Tang , Lingyu Liang , Yining Huang , Haojie Li , Shuangping Huang

This paper proposes a talking face generation method named "CP-EB" that takes an audio signal as input and a person image as reference, to synthesize a photo-realistic people talking video with head poses controlled by a short video clip…

Computer Vision and Pattern Recognition · Computer Science 2023-11-16 Jianzong Wang , Yimin Deng , Ziqi Liang , Xulong Zhang , Ning Cheng , Jing Xiao

We present VideoReTalking, a new system to edit the faces of a real-world talking head video according to input audio, producing a high-quality and lip-syncing output video even with a different emotion. Our system disentangles this…

Computer Vision and Pattern Recognition · Computer Science 2022-11-29 Kun Cheng , Xiaodong Cun , Yong Zhang , Menghan Xia , Fei Yin , Mingrui Zhu , Xuan Wang , Jue Wang , Nannan Wang

Vivid talking face generation holds immense potential applications across diverse multimedia domains, such as film and game production. While existing methods accurately synchronize lip movements with input audio, they typically ignore…

Computer Vision and Pattern Recognition · Computer Science 2024-06-13 Jiadong Liang , Feng Lu

Audio-driven talking head generation aims to create vivid and realistic videos from a static portrait and speech. Existing AR-based methods rely on intermediate facial representations, which limit their expressiveness and realism.…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Yuzhe Weng , Haotian Wang , Yuanhong Yu , Jun Du , Shan He , Xiaoyan Wu , Haoran Xu

While recent research has made significant progress in speech-driven talking face generation, the quality of the generated video still lags behind that of real recordings. One reason for this is the use of handcrafted intermediate…

Computer Vision and Pattern Recognition · Computer Science 2025-04-08 Chenpeng Du , Qi Chen , Tianyu He , Xu Tan , Xie Chen , Kai Yu , Sheng Zhao , Jiang Bian

One-shot talking head generation produces lip-sync talking heads based on arbitrary audio and one source face. To guarantee the naturalness and realness, recent methods propose to achieve free pose control instead of simply editing mouth…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Jin Liu , Xi Wang , Xiaomeng Fu , Yesheng Chai , Cai Yu , Jiao Dai , Jizhong Han

The challenge of talking face generation from speech lies in aligning two different modal information, audio and video, such that the mouth region corresponds to input audio. Previous methods either exploit audio-visual representation…

Computer Vision and Pattern Recognition · Computer Science 2022-11-04 Se Jin Park , Minsu Kim , Joanna Hong , Jeongsoo Choi , Yong Man Ro

Creating realistic, natural, and lip-readable talking face videos remains a formidable challenge. Previous research primarily concentrated on generating and aligning single-frame images while overlooking the smoothness of frame-to-frame…

Computer Vision and Pattern Recognition · Computer Science 2024-05-29 Shuheng Ge , Haoyu Xing , Li Zhang , Xiangqian Wu

Talking face generation aims to synthesize realistic speaking portraits from a single image, yet existing methods often rely on explicit optical flow and local warping, which fail to model complex global motions and cause identity drift. We…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Bo Chen , Tao Liu , Qi Chen , Xie Chen , Zilong Zheng

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

In this paper, we introduce a simple and novel framework for one-shot audio-driven talking head generation. Unlike prior works that require additional driving sources for controlled synthesis in a deterministic manner, we instead…

Graphics · Computer Science 2022-12-09 Zhentao Yu , Zixin Yin , Deyu Zhou , Duomin Wang , Finn Wong , Baoyuan Wang

Audio-driven talking face generation aims to synthesize video with lip movements synchronized to input audio. However, current generative techniques face challenges in preserving intricate regional textures (skin, teeth). To address the…

Computer Vision and Pattern Recognition · Computer Science 2024-09-06 Lingyu Xiong , Xize Cheng , Jintao Tan , Xianjia Wu , Xiandong Li , Lei Zhu , Fei Ma , Minglei Li , Huang Xu , Zhihu Hu

This paper introduces a new control signal for facial motion generation: timeline control. Compared to audio and text signals, timelines provide more fine-grained control, such as generating specific facial motions with precise timing.…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Yifeng Ma , Jinwei Qi , Chaonan Ji , Peng Zhang , Bang Zhang , Zhidong Deng , Liefeng Bo

Implementing fine-grained emotion control is crucial for emotion generation tasks because it enhances the expressive capability of the generative model, allowing it to accurately and comprehensively capture and express various nuanced…

Computer Vision and Pattern Recognition · Computer Science 2024-02-05 Guanwen Feng , Haoran Cheng , Yunan Li , Zhiyuan Ma , Chaoneng Li , Zhihao Qian , Qiguang Miao , Chi-Man Pun

Speech-driven facial animation is the process which uses speech signals to automatically synthesize a talking character. The majority of work in this domain creates a mapping from audio features to visual features. This often requires…

Audio and Speech Processing · Electrical Eng. & Systems 2018-07-20 Konstantinos Vougioukas , Stavros Petridis , Maja Pantic