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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 1–25 of 204 papers

TitleStatusHype
InstructFLIP: Exploring Unified Vision-Language Model for Face Anti-spoofingCode1
Multi-Modal Face Anti-Spoofing via Cross-Modal Feature Transitions—0
Leveraging Intermediate Features of Vision Transformer for Face Anti-Spoofing—0
FaceShield: Explainable Face Anti-Spoofing with Multimodal Large Language Models—0
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing—0
Learning Unknown Spoof Prompts for Generalized Face Anti-Spoofing Using Only Real Face Images—0
Generative Classifier for Domain Generalization—0
Optimal Transport-Guided Source-Free Adaptation for Face Anti-Spoofing—0
Enhancing Learnable Descriptive Convolutional Vision Transformer for Face Anti-SpoofingCode0
Unsupervised Feature Disentanglement and Augmentation Network for One-class Face Anti-spoofing—0
SLIP: Spoof-Aware One-Class Face Anti-Spoofing with Language Image PretrainingCode0
DADM: Dual Alignment of Domain and Modality for Face Anti-spoofing—0
Extended monocular 3D imaging—0
FoundPAD: Foundation Models Reloaded for Face Presentation Attack DetectionCode1
Interpretable Face Anti-Spoofing: Enhancing Generalization with Multimodal Large Language Models—0
Deep Change Monitoring: A Hyperbolic Representative Learning Framework and a Dataset for Long-term Fine-grained Tree Change DetectionCode1
BIG-MoE: Bypass Isolated Gating MoE for Generalized Multimodal Face Anti-SpoofingCode0
Concept Discovery in Deep Neural Networks for Explainable Face Anti-Spoofing—0
FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation LearningCode2
Confidence Aware Learning for Reliable Face Anti-spoofing—0
A Multi-Modal Approach for Face Anti-Spoofing in Non-Calibrated Systems using Disparity Maps—0
DiffFAS: Face Anti-Spoofing via Generative Diffusion ModelsCode1
Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data SynthesisCode0
Time-Aware Face Anti-Spoofing with Rotation Invariant Local Binary Patterns and Deep Learning—0
Re-evaluation of Face Anti-spoofing Algorithm in Post COVID-19 Era Using Mask Based Occlusion Attack—0
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