Test-time domain generalization for face anti-spoofing
Abstract Face Anti-Spoofing (FAS) is pivotal in safeguarding facial recognition systems
against presentation attacks. While domain generalization (DG) methods have been …
against presentation attacks. While domain generalization (DG) methods have been …
TF-FAS: twofold-element fine-grained semantic guidance for generalizable face anti-spoofing
Generalizable Face anti-spoofing (FAS) approaches have recently garnered considerable
attention due to their robustness in unseen scenarios. Some recent methods incorporate …
attention due to their robustness in unseen scenarios. Some recent methods incorporate …
Meta curvature-aware minimization for domain generalization
Domain generalization (DG) aims to enhance the ability of models trained on source
domains to generalize effectively to unseen domains. Recently, Sharpness-Aware …
domains to generalize effectively to unseen domains. Recently, Sharpness-Aware …
Generalized Face Liveness Detection via De-fake Face Generator
Previous Face Anti-spoofing (FAS) methods face the challenge of generalizing to unseen
domains, mainly because most existing FAS datasets are relatively small and lack data …
domains, mainly because most existing FAS datasets are relatively small and lack data …
GVformer: Graph Guided Video Vision Transformer for Face Anti-Spoofing
In videos containing spoofed faces, we may uncover the spoofing evidence based on either
photometric or dynamic abnormality, even a combination of both. Prevailing face anti …
photometric or dynamic abnormality, even a combination of both. Prevailing face anti …
Enhancing face anti-spoofing through domain generalization with nonlinear spinning neural P neuron fusion and dual feature extractors
X You, Y Wang, X Zhao - Computers and Electrical Engineering, 2025 - Elsevier
Face anti-spoofing (FAS) is the key to ensuring the security of the face recognition system. In
recent years, some FAS methods based on deep learning have achieved good results in …
recent years, some FAS methods based on deep learning have achieved good results in …
Interpretable Face Anti-Spoofing: Enhancing Generalization with Multimodal Large Language Models
Face Anti-Spoofing (FAS) is essential for ensuring the security and reliability of facial
recognition systems. Most existing FAS methods are formulated as binary classification …
recognition systems. Most existing FAS methods are formulated as binary classification …
Face Forgery Detection with Elaborate Backbone
Face Forgery Detection (FFD), or Deepfake detection, aims to determine whether a digital
face is real or fake. Due to different face synthesis algorithms with diverse forgery patterns …
face is real or fake. Due to different face synthesis algorithms with diverse forgery patterns …
Confidence Aware Learning for Reliable Face Anti-spoofing
Current Face Anti-spoofing (FAS) models tend to make overly confident predictions even
when encountering unfamiliar scenarios or unknown presentation attacks, which leads to …
when encountering unfamiliar scenarios or unknown presentation attacks, which leads to …
FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning
This work asks: with abundant, unlabeled real faces, how to learn a robust and transferable
facial representation that boosts various face security tasks with respect to generalization …
facial representation that boosts various face security tasks with respect to generalization …