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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 151–175 of 204 papers

TitleStatusHype
Unified Physical-Digital Attack Detection Challenge—0
Unsupervised Compound Domain Adaptation for Face Anti-Spoofing—0
Unsupervised Feature Disentanglement and Augmentation Network for One-class Face Anti-spoofing—0
Use of in-the-wild images for anomaly detection in face anti-spoofing—0
Visual Prompt Flexible-Modal Face Anti-Spoofing—0
A Dataset and Benchmark Towards Multi-Modal Face Anti-Spoofing Under Surveillance Scenarios—0
Cross-ethnicity Face Anti-spoofing Recognition Challenge: A Review—0
DADM: Dual Alignment of Domain and Modality for Face Anti-spoofing—0
A-DeepPixBis: Attentional Angular Margin for Face Anti-Spoofing—0
Deep Frequent Spatial Temporal Learning for Face Anti-Spoofing—0
Advancing Cross-Domain Generalizability in Face Anti-Spoofing: Insights, Design, and Metrics—0
Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models—0
Deep Transfer Across Domains for Face Anti-spoofing—0
Adversarial Unsupervised Domain Adaptation Guided with Deep Clustering for Face Presentation Attack Detection—0
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing—0
Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofing—0
Distributional Estimation of Data Uncertainty for Surveillance Face Anti-spoofing—0
Wild Face Anti-Spoofing Challenge 2023: Benchmark and ResultsCode0
FeatherNets: Convolutional Neural Networks as Light as Feather for Face Anti-spoofingCode0
AdvFAS: A robust face anti-spoofing framework against adversarial examplesCode0
A personalized benchmark for face anti-spoofingCode0
A visualization method for data domain changes in CNN networks and the optimization method for selecting thresholds in classification tasksCode0
Bi-FPNFAS: Bi-Directional Feature Pyramid Network for Pixel-Wise Face Anti-Spoofing by Leveraging Fourier SpectraCode0
BIG-MoE: Bypass Isolated Gating MoE for Generalized Multimodal Face Anti-SpoofingCode0
A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofingCode0
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