DeepFaceGen

A large-scale evaluation benchmark called DeepFaceGen, aimed at quantitatively assessing the effectiveness of face forgery detection and facilitating the iterative development of forgery detection technology. DeepFaceGen consists of 776, 990 real face image/video samples and 773, 812 face forgery image/video samples, generated using 35 mainstream face generation techniques.

搜集汇总

背景与挑战

背景概述

DeepFaceGen是一个大规模的人脸伪造检测评估基准，包含超过150万的真实与伪造人脸图像/视频样本，这些样本由34种主流人脸生成技术生成，旨在定量评估检测效果并推动技术迭代发展。