  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 contrary, 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).
