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Generative Face Video Coding Techniques and Standardization Efforts: A Review

  • Bolin Chen*
  • , Jie Chen
  • , Shiqi Wang
  • , Yan Ye
  • *此作品的通讯作者
  • City University of Hong Kong
  • Alibaba Group Holding Ltd.

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Generative Face Video Coding (GFVC) techniques can exploit the compact representation of facial priors and the strong inference capability of deep generative models, achieving high-quality face video communication in ultra-low bandwidth scenarios. This paper conducts a comprehensive survey on the recent advances of the GFVC techniques and standardization efforts, which could be applicable to ultra low bitrate communication, user-specified animation/filtering and metaverse-related functionalities. In particular, we generalize GFVC systems within one coding framework and summarize different GFVC algorithms with their corresponding visual representations. Moreover, we review the GFVC standardization activities that are specified with supplemental enhancement information messages. Finally, we discuss fundamental challenges and broad applications on GFVC techniques and their standardization potentials, as well as envision their future trends. The project page can be found at https://github.com/Berlin0610/Awesome-Generative-Face-Video-Coding.

源语言英语
主期刊名Proceedings - DCC 2024
主期刊副标题2024 Data Compression Conference
编辑Ali Bilgin, James E. Fowler, Joan Serra-Sagrista, Yan Ye, James A. Storer
出版商Institute of Electrical and Electronics Engineers Inc.
103-112
页数10
ISBN(电子版)9798350385878
DOI
出版状态已出版 - 2024
已对外发布
活动2024 Data Compression Conference, DCC 2024 - Snowbird, 美国
期限: 19 3月 202422 3月 2024

出版系列

姓名Data Compression Conference Proceedings
ISSN(印刷版)1068-0314

会议

会议2024 Data Compression Conference, DCC 2024
国家/地区美国
Snowbird
时期19/03/2422/03/24

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