Face Liveness Detection Based on Client Identity Using Siamese Network
Face liveness detection is an essential prerequisite for face recognition applications. Previous face liveness detection methods usually train a binary classifier to differentiate between a fake face and a real face before face recognition. The client identity information is not utilized in previous face liveness detection methods. However, in practical face recognition applications, face spoofing attacks are always aimed at a specific client, and the client identity information can provide useful clues for face liveness detection. In this paper, we propose a face liveness detection method based on the client identity using Siamese network. We detect face liveness after face recognition instead of before face recognition, that is, we detect face liveness with the client identity information. We train a Siamese network with image pairs. Each image pair consists of two real face images or one real and one fake face images. The face images in each pair come from a same client. Given a test face image, the face image is firstly recognized by face recognition system, then the real face image of the identified client is retrieved to help the face liveness detection. Experiment results demonstrate the effectiveness of our method.
Code (3)
Tasks
Face RecognitionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
An Ensemble Model for Face Liveness Detection
In this paper, we present a passive method to detect face presentation attack a.k.a face liveness detection using an ensemble deep learning technique. Face liveness detection is one of the key steps involved in user iden…
modelGeneralized Face Anti-spoofing via Finer Domain Partition and Disentangling Liveness-irrelevant Factors
Face anti-spoofing techniques based on domain generalization have recently been studied widely. Adversarial learning and meta-learning techniques have been adopted to learn domain-invariant representations. However, prio…
DiversityDomain GeneralizationFace Anti-SpoofingMeta-LearningAn Overview of Face Liveness Detection
Face recognition is a widely used biometric approach. Face recognition technology has developed rapidly in recent years and it is more direct, user friendly and convenient compared to other methods. But face recognition …
Face RecognitionSwap It Like Its Hot: Segmentation-based spoof attacks on eye-tracking images
Video-based eye trackers capture the iris biometric and enable authentication to secure user identity. However, biometric authentication is susceptible to spoofing another user's identity through physical or digital mani…
CLIPC8: Face liveness detection algorithm based on image-text pairs and contrastive learning
Face recognition technology is widely used in the financial field, and various types of liveness attack behaviors need to be addressed. Existing liveness detection algorithms are trained on specific training datasets and…
Contrastive LearningFace Recognition