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One-shot motion talking head generation with audio-driven model

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成果类型:
期刊论文
作者:
Peng Tang;Huihuang Zhao*;Weiliang Meng;Yaonan Wang
通讯作者:
Huihuang Zhao
作者机构:
[Peng Tang; Huihuang Zhao] Hengyang Normal University, College of Computer Science and Technology, Hengyang, 421002, Hunan, China
[Weiliang Meng] University of Chinese Academy of Sciences, School of Artificial Intelligence, Beijing, 100049, China
[Yaonan Wang] Hunan University, National Engineering Laboratory for Robot Visual Perception and Control Technology, Changsha, 410082, Hunan, China
通讯机构:
[Huihuang Zhao] H
Hengyang Normal University, College of Computer Science and Technology, Hengyang, 421002, Hunan, China
语种:
英文
期刊:
Expert Systems with Applications
ISSN:
0957-4174
年:
2026
卷:
297
页码:
129344
基金类别:
CRediT authorship contribution statement Peng Tang: Conceptualization, Methodology, Software, Formal analysis, Writing – original draft; Huihuang Zhao: Supervision, Project administration, acquisition, Writing – review & editing; Weiliang Meng: Data curation, Validation, Visualization, Investigation; Yaonan Wang: Supervision, Resources, Writing – review & editing.
机构署名:
本校为第一且通讯机构
院系归属:
计算机科学与技术学院
摘要:
Exciting achievements have been made in audio-driven face-talking head generation. However, while existing methods excel at generating a speaking head from a frontal identity image, generating a speaking head with a head pose does not yield satisfactory results when the identity is based on a side image of the face. To address this limitation, a concise and effective approach is proposed in this work. Our method generates efficient talking head videos using a side face image as the identity. It uses facial features and head posture to predict frontal keypoints, during which facial expression f...

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