2026-10-14T14:53:11Z https://www.scidb.cn/oai

10.57760/sciencedb.j00240.00096 2026-01-20T08:43:56Z

2026-01-20 Self-Cropped FaceForensics++ Dataset for Face Fraud Detection doi:10.57760/sciencedb.j00240.00096 en The facial image data used in this study is based on the FaceForensics++ (FF++) public dataset (Rössler et al., 2019), which contains 1000 real videos and 4000 forged videos, covering five typical deep forgery methods (DeepFakes, Face2Face, FaceSwap, NeuralTextures, FaceShifter). We use the MTCNN (Multi-task Convolutional Neural Network) face detection algorithm to extract frames (with a sampling rate of 2 frames per second) from the FF++ videos and automatically crop the face region images. All cropped face images are uniformly adjusted to 256×256 pixels. Deepfake ; face presentation attack detection; dataset; face image huang yuan xuan 振宇 PUBLIC https://creativecommons.org/licenses/by-nc-nd/4.0/ dataset Science Data Bank