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

2021/02/18 by Liming Jiang, Zhengkui Guo, Jiang, Liming +40 · 1 citation
Computer Science · #Anomaly Detection Techniques and Applications #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Face recognition and analysis #Generative Adversarial Networks and Image Synthesis #Machine Learning (cs.LG) #cs.CV #cs.LG

paper · pdf · doi:10.48550/arxiv.2102.09471

Technical report. Challenge website: https://competitions.codalab.org/competitions/25228

arxiv created 2021/02/18 · openalex publication_date 2021/02/18 · arxiv updated 2021/02/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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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