TY - GEN
T1 - DFGC 2022
T2 - 2022 IEEE International Joint Conference on Biometrics, IJCB 2022
AU - Peng, Bo
AU - Xiang, Wei
AU - Jiang, Yue
AU - Wang, Wei
AU - Dong, Jing
AU - Sun, Zhenan
AU - Lei, Zhen
AU - Lyu, Siwei
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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 Deep-Fake 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).
AB - 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 Deep-Fake 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).
UR - https://www.scopus.com/pages/publications/85147250836
U2 - 10.1109/IJCB54206.2022.10007991
DO - 10.1109/IJCB54206.2022.10007991
M3 - Conference contribution
AN - SCOPUS:85147250836
T3 - 2022 IEEE International Joint Conference on Biometrics, IJCB 2022
BT - 2022 IEEE International Joint Conference on Biometrics, IJCB 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 10 October 2022 through 13 October 2022
ER -