This project forked from zeusees/hyperfas
静默活体检测 Silent Face Anti-Spoofing Attack Detection
Home Page: http://www.zeusee.com
License: BSD 3-Clause "New" or "Revised" License
人脸活体验证是人脸识别过程中重要的一环，主要用以区分真实人脸与假脸图像，能够识别利用纸张打印、屏幕翻拍、3D模型等方式的欺骗行为。我们在算法设计阶段，尝试了不同的方法，包括：SVM、LBP、深度学习等。针对单一场景或者摄像头，能够得到不错的效果，但是没有得到一个能够适配多种摄像头的活体算法，这里我们将其中一个较好模型开放出来，但是在逆光等情况下效果依然不是很好，大家可以作为参考。
这个模型大约采用了36w张图像，其中假脸18w张，真脸18w万张，包括纸张、屏幕，也采用了大部分公开的假脸数据集。
基于mobilenet-0.5
OpenCV 3.4.3+
MTCNN人脸检测
Keras，TF
Python3
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