DFGC 2021: A DeepFake Game Competition
This work addresses the need for standardized evaluation in DeepFake research, though it is incremental as it builds on existing competition frameworks.
The paper summarizes the DFGC 2021 competition, which tackled the adversarial game between DeepFake creation and detection methods by providing a common benchmarking platform, resulting in the release of a testing dataset to benefit the research community.
This paper presents a summary of the DFGC 2021 competition. DeepFake technology is developing fast, and realistic face-swaps are increasingly deceiving and hard to detect. At the same time, DeepFake detection methods are also improving. There is a two-party game between DeepFake creators and detectors. This competition provides a common platform for benchmarking the adversarial game between current state-of-the-art DeepFake creation and detection methods. In this paper, we present the organization, results and top solutions of this competition and also share our insights obtained during this event. We also release the DFGC-21 testing dataset collected from our participants to further benefit the research community.