DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results
This is an incremental challenge that addresses the problem of detecting forged faces in videos for security and media integrity applications.
The paper reports on the DeeperForensics Challenge 2020, which tackled real-world face forgery detection using a dataset of 60,000 videos and 17.6 million frames, with 115 participants and 25 teams submitting solutions, and it summarizes the winning methods and discusses future research directions.
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.