DFGC 2021: A DeepFake Game Competition
Bo Peng
Hongxing Fan
Wei Wang
Jing Dong
Yuezun Li
Siwei Lyu
Qi Li
Zhenan Sun
Han Chen
Baoying Chen
Yanjie Hu
Shenghai Luo
Junrui Huang
Yutong Yao
Boyuan Liu
H. Ling
Guosheng Zhang
Zhi-liang Xu
Changtao Miao
Changlei Lu
Shan He
Xiaoyu Wu
Wanyi Zhuang

Abstract
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.
View on arXivComments on this paper