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Face Anti-Spoofing
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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.
<span style="color:grey; opacity: 0.6">( Image credit: Learning Generalizable and Identity-Discriminative Representations for Face Anti-Spoofing )</span>
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Multi-Modal Face Anti-Spoofing via Cross-Modal Feature Transitions
Leveraging Intermediate Features of Vision Transformer for Face Anti-Spoofing
FaceShield: Explainable Face Anti-Spoofing with Multimodal Large Language Models
Denoising and Alignment: Rethinking Domain Generalization for Multimodal Face Anti-Spoofing
Learning Unknown Spoof Prompts for Generalized Face Anti-Spoofing Using Only Real Face Images
Generative Classifier for Domain Generalization
Unsupervised Feature Disentanglement and Augmentation Network for One-class Face Anti-spoofing
Enhancing Learnable Descriptive Convolutional Vision Transformer for Face Anti-Spoofing
Optimal Transport-Guided Source-Free Adaptation for Face Anti-Spoofing
SLIP: Spoof-Aware One-Class Face Anti-Spoofing with Language Image Pretraining
DADM: Dual Alignment of Domain and Modality for Face Anti-spoofing
Extended monocular 3D imaging
FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection
Interpretable Face Anti-Spoofing: Enhancing Generalization with Multimodal Large Language Models
BIG-MoE: Bypass Isolated Gating MoE for Generalized Multimodal Face Anti-Spoofing
Concept Discovery in Deep Neural Networks for Explainable Face Anti-Spoofing
FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning
Confidence Aware Learning for Reliable Face Anti-spoofing
A Multi-Modal Approach for Face Anti-Spoofing in Non-Calibrated Systems using Disparity Maps
DiffFAS: Face Anti-Spoofing via Generative Diffusion Models
Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data Synthesis
Time-Aware Face Anti-Spoofing with Rotation Invariant Local Binary Patterns and Deep Learning
Re-evaluation of Face Anti-spoofing Algorithm in Post COVID-19 Era Using Mask Based Occlusion Attack
G$^2$V$^2$former: Graph Guided Video Vision Transformer for Face Anti-Spoofing
Generalized Face Anti-spoofing via Finer Domain Partition and Disentangling Liveness-irrelevant Factors
Liveness Detection in Computer Vision: Transformer-based Self-Supervised Learning for Face Anti-Spoofing
Advancing Cross-Domain Generalizability in Face Anti-Spoofing: Insights, Design, and Metrics
Principles of Designing Robust Remote Face Anti-Spoofing Systems
Supervised Contrastive Learning for Snapshot Spectral Imaging Face Anti-Spoofing
Adversarial Attacks on Both Face Recognition and Face Anti-spoofing Models
RGB Guided ToF Imaging System: A Survey of Deep Learning-based Methods
Hyp-OC: Hyperbolic One Class Classification for Face Anti-Spoofing
A visualization method for data domain changes in CNN networks and the optimization method for selecting thresholds in classification tasks
FaceCat: Enhancing Face Recognition Security with a Unified Diffusion Model
Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Clues
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