DFGC 2022: The Second DeepFake Game Competition

被引:8
作者
Peng, Bo [1 ]
Xiang, Wei [1 ]
Jiang, Yue [1 ]
Wang, Wei [1 ]
Dong, Jing [1 ]
Sun, Zhenan [1 ]
Lei, Zhen [2 ]
Lyu, Siwei [3 ]
机构
[1] Chinese Acad Sci, Ctr Res Intelligent Percept & Comp CRIPAC, Inst Automat, Beijing 100190, Peoples R China
[2] Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100190, Peoples R China
[3] Univ Buffalo State Univ New York, Buffalo, NY 14260 USA
来源
2022 IEEE INTERNATIONAL JOINT CONFERENCE ON BIOMETRICS (IJCB) | 2022年
基金
中国国家自然科学基金;
关键词
D O I
10.1109/IJCB54206.2022.10007991
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents the summary report on our DFGC 2022 competition. The DeepFake is rapidly evolving, and realistic face-swaps are becoming more deceptive and difficult to detect. On the other hand, methods for detecting DeepFakes are also improving. There is a two-party game between DeepFake creators and defenders. This competition provides a common platform for benchmarking the game between the current state-of-the-arts in DeepFake creation and detection methods. The main research question to be answered by this competition is the current state of the two adversaries when competed with each other. This is the second edition after the last year's DFGC 2021, with a new, more diverse video dataset, a more realistic game setting, and more reasonable evaluation metrics. With this competition, we aim to stimulate research ideas for building better defenses against the DeepFake threats. We also release our DFGC 2022 dataset contributed by both our participants and ourselves to enrich the DeepFake data resources for the research community (https://github.com/NiCE-X/DFGC- 2022).
引用
收藏
页数:10
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