This paper reports methods and results in the DeeperForensics Challenge 2020 on real-world face forgery detection. The challenge employs the DeeperForensics-1.0 dataset, one of the most extensive publicly available real-world face forgery detection datasets, with 60,000 videos constituted by a total of 17.6 million frames. The model evaluation is conducted online on a high-quality hidden test set with multiple sources and diverse distortions. A total of 115 participants registered for the competition, and 25 teams made valid submissions. We will summarize the winning solutions and present some discussions on potential research directions.
@article{arxiv.2102.09471,
title = {DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results},
author = {Liming Jiang and Zhengkui Guo and Wayne Wu and Zhaoyang Liu and Ziwei Liu and Chen Change Loy and Shuo Yang and Yuanjun Xiong and Wei Xia and Baoying Chen and Peiyu Zhuang and Sili Li and Shen Chen and Taiping Yao and Shouhong Ding and Jilin Li and Feiyue Huang and Liujuan Cao and Rongrong Ji and Changlei Lu and Ganchao Tan},
journal= {arXiv preprint arXiv:2102.09471},
year = {2021}
}