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.
@article{arxiv.2106.01217,
title = {DFGC 2021: A DeepFake Game Competition},
author = {Bo Peng and Hongxing Fan and Wei Wang and Jing Dong and Yuezun Li and Siwei Lyu and Qi Li and Zhenan Sun and Han Chen and Baoying Chen and Yanjie Hu and Shenghai Luo and Junrui Huang and Yutong Yao and Boyuan Liu and Hefei Ling and Guosheng Zhang and Zhiliang Xu and Changtao Miao and Changlei Lu and Shan He and Xiaoyan Wu and Wanyi Zhuang},
journal= {arXiv preprint arXiv:2106.01217},
year = {2021}
}