Face Spoofing Using Deep Learning

We propose a novel framework based on the Convolutional Neural Network for the face anti-spoofing problem, which is inspired by the philosophy used by humans to determine whether a presented face example is genuine or not, namely, to look at the example globally first and then carefully observe the local regions to gain more discriminative information (CNN). Specifically, we use deep learning to mimic the behavior of discovering face-spoofing-related information from image sub-patches.