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Face Anti-Spoofing

Facial anti-spoofing is the task of preventing false facial verification by using a photo, video, mask or a different substitute for an authorized person’s face. Some examples of attacks:

  • Print attack: The attacker uses someone’s photo. The image is printed or displayed on a digital device.

  • Replay/video attack: A more sophisticated way to trick the system, which usually requires a looped video of a victim’s face. This approach ensures behaviour and facial movements to look more ‘natural’ compared to holding someone’s photo.

  • 3D mask attack: During this type of attack, a mask is used as the tool of choice for spoofing. It’s an even more sophisticated attack than playing a face video. In addition to natural facial movements, it enables ways to deceive some extra layers of protection such as depth sensors.

( Image credit: Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing )

Papers

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Showing 51–75 of 204 papers

TitleStatusHype
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing—0
Adversarial Unsupervised Domain Adaptation Guided with Deep Clustering for Face Presentation Attack Detection—0
FaceShield: Explainable Face Anti-Spoofing with Multimodal Large Language Models—0
Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing—0
Distributional Estimation of Data Uncertainty for Surveillance Face Anti-spoofing—0
Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofing—0
Domain Agnostic Feature Learning for Image and Video Based Face Anti-spoofing—0
Domain Generalization Guided by Gradient Signal to Noise Ratio of Parameters—0
FaceSkin: A Privacy Preserving Facial skin patch Dataset for multi Attributes classification—0
Domain Generalization with Pseudo-Domain Label for Face Anti-Spoofing—0
Deep Transfer Across Domains for Face Anti-spoofing—0
Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models—0
Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cues—0
Adaptive Mixture of Experts Learning for Generalizable Face Anti-Spoofing—0
Face Presentation Attack Detection—0
Federated Face Presentation Attack Detection—0
Advancing Cross-Domain Generalizability in Face Anti-Spoofing: Insights, Design, and Metrics—0
Face Anti-Spoofing: Model Matters, so Does Data—0
Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing—0
Aurora Guard: Reliable Face Anti-Spoofing via Mobile Lighting System—0
Adaptive-avg-pooling based Attention Vision Transformer for Face Anti-spoofing—0
Face Anti-Spoofing Via Disentangled Representation Learning—0
DADM: Dual Alignment of Domain and Modality for Face Anti-spoofing—0
Aurora Guard: Real-Time Face Anti-Spoofing via Light Reflection—0
Attention-Based Face AntiSpoofing of RGB Images, using a Minimal End-2-End Neural Network—0
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