OpenForensics Face Forgery Detection Dataset

The OpenForensics dataset is a large-scale challenging dataset designed for multi-faceted forgery detection and segmentation tasks. It was released in 2021 by researchers from the National Institute of Informatics, SOKENDAI, and the University of Tokyo. The related paper results are "OpenForensics: Large-Scale Challenging Dataset For Multi-Face Forgery Detection And Segmentation In-The-Wild".

The dataset consists of 115K wild images and 334K faces, all of which have rich facial annotations, including forgery categories, bounding boxes, segmentation masks, forgery boundaries, and general facial landmarks, and contains various backgrounds and multiple people of different ages, genders, poses, positions, and facial occlusions. This dataset not only supports multi-face forgery detection and segmentation tasks, but also supports general tasks involving general faces, and has great potential for research on deep forgery prevention and general human face detection.