MFFI is a 1,024,000-image face forgery benchmark spanning 50 (listed 51) forgery techniques, varied facial scenes, multiple real-data sources, and multi-level degradation operations.
Multi-Forgery Detection Challenge 2022: Push the Frontier of Unconstrained and Diverse Forgery Detection
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abstract
In this paper, we present the Multi-Forgery Detection Challenge held concurrently with the IEEE Computer Society Workshop on Biometrics at CVPR 2022. Our Multi-Forgery Detection Challenge aims to detect automatic image manipulations including but not limited to image editing, image synthesis, image generation, image photoshop, etc. Our challenge has attracted 674 teams from all over the world, with about 2000 valid result submission counts. We invited the Top 10 teams to present their solutions to the challenge, from which three teams are awarded prizes in the grand finale. In this paper, we present the solutions from the Top 3 teams, in order to boost the research work in the field of image forgery detection.
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MFFI: Multi-Dimensional Face Forgery Image Dataset for Real-World Scenarios
MFFI is a 1,024,000-image face forgery benchmark spanning 50 (listed 51) forgery techniques, varied facial scenes, multiple real-data sources, and multi-level degradation operations.