DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results

• URL: http://arxiv.org/abs/2102.09471v1
• Date: Thu, 18 Feb 2021 16:48:57 GMT
• Title: DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results
• Authors: Liming Jiang, Zhengkui Guo, Wayne Wu, Zhaoyang Liu, Ziwei Liu, Chen Change Loy, Shuo Yang, Yuanjun Xiong, Wei Xia, Baoying Chen, Peiyu Zhuang, Sili Li, Shen Chen, Taiping Yao, Shouhong Ding, Jilin Li, Feiyue Huang, Liujuan Cao, Rongrong Ji, Changlei Lu, Ganchao Tan
• Abstract summary: 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, with 60,000 videos constituted by a total of 17.6 million frames. A total of 115 participants registered for the competition, and 25 teams made valid submissions.
• Score: 144.5252578415748
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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