mlsanityData to 14 Oct 2026

Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofing

arXiv 2112.14894 ↗First posted 30 Dec 2021cs.CV cs.CRcited by 23

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Abstract (arXiv)

Although existing face anti-spoofing (FAS) methods achieve high accuracy in intra-domain experiments, their effects drop severely in cross-domain scenarios because of poor generalization. Recently, multifarious techniques have been explored, such as domain generalization and representation disentanglement. However, the improvement is still limited by two issues: 1) It is difficult to perfectly map all faces to a shared feature space. If faces from unknown domains are not mapped to the known region in the shared feature space, accidentally inaccurate predictions will be obtained. 2) It is hard to completely consider various spoof traces for disentanglement. In this paper, we propose a Feature Generation and Hypothesis Verification framework to alleviate the two issues. Above all, feature generation networks which generate hypotheses of real faces and known attacks are introduced for the first time in the FAS task. Subsequently, two hypothesis verification modules are applied to judge whether the input face comes from the real-face space and the real-face distribution respectively. Furthermore, some analyses of the relationship between our framework and Bayesian uncertainty estimation are given, which provides theoretical support for reliable defense in unknown domains. Experimental results show our framework achieves promising results and outperforms the state-of-the-art approaches on extensive public datasets.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). Builds on 34 of its 66 references that are in the map. First posted on arXiv 30 Dec 2021.

Builds on

34 of 66 references.

References · 34

  1. 2015Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learningcited by 4,448
  2. 2016Simple and Scalable Predictive Uncertainty Estimation using Deep Ensemblescited by 3,926
  3. 2017What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision?cited by 2,352
  4. 2017Unsupervised Anomaly Detection with Generative Adversarial Networks to Guide Marker Discoverycited by 566
  5. 2020Searching Central Difference Convolutional Networks for Face Anti-Spoofingcited by 173
  6. 2018Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervisioncited by 167
  7. 2020Single-Side Domain Generalization for Face Anti-Spoofingcited by 139
  8. 2018Sequential Attend, Infer, Repeat: Generative Modelling of Moving Objectscited by 128
  9. 2021Pixel-wise Anomaly Detection in Complex Driving Scenescited by 109
  10. 2020NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofingcited by 105
  11. 2015face anti-spoofing based on color texture analysiscited by 82
  12. 2014Learn Convolutional Neural Network for Face Anti-Spoofingcited by 80
22 more
  1. 2019Deep Tree Learning for Zero-shot Face Anti-Spoofingcited by 73
  2. 2020Face Anti-Spoofing Via Disentangled Representation Learningcited by 65
  3. 2020Face Anti-Spoofing with Human Material Perceptioncited by 62
  4. 2020On Disentangling Spoof Trace for Generic Face Anti-Spoofingcited by 62
  5. 2021Self-Domain Adaptation for Face Anti-Spoofingcited by 49
  6. 2021Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofingcited by 49
  7. 2021Dual Reweighting Domain Generalization for Face Presentation Attack Detectioncited by 47
  8. 2021Generalizable Representation Learning for Mixture Domain Face Anti-Spoofingcited by 46
  9. 2020Revisiting Pixel-Wise Supervision for Face Anti-Spoofingcited by 45
  10. 2019Learning Meta Model for Zero- and Few-shot Face Anti-spoofingcited by 44
  11. 2021TransRPPG: Remote Photoplethysmography Transformer for 3D Mask Face Presentation Attack Detectioncited by 41
  12. 2019Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learningcited by 37
  13. 2020Multi-Modal Face Anti-Spoofing Based on Central Difference Networkscited by 36
  14. 2021Disentangled High Quality Salient Object Detectioncited by 35
  15. 2021Meta-Teacher For Face Anti-Spoofingcited by 33
  16. 2021Structure Destruction and Content Combination for Face Anti-Spoofingcited by 18
  17. 2020Noise Modeling, Synthesis and Classification for Generic Object Anti-Spoofingcited by 14
  18. 2019Bidirectional Inference Networks: A Class of Deep Bayesian Networks for Health Profilingcited by 11
  19. 2021Aurora Guard: Reliable Face Anti-Spoofing via Mobile Lighting Systemcited by 9
  20. 2021Few-Shot Domain Expansion for Face Anti-Spoofingcited by 7
  21. 2018Uncertainty Estimations by Softplus normalization in Bayesian Convolutional Neural Networks with Variational Inferencecited by 2
  22. 2021Domain Generalization with Pseudo-Domain Label for Face Anti-Spoofingcited by 2

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 5; 2023: 8; 2024: 5; 2025: 4; 2026: 1.

23 papers.

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  1. 2023FLIP: Cross-domain Face Anti-spoofing with Language Guidancecited by 45
  2. 2022Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofingcited by 38
  3. 2024FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learningcited by 23
  4. 2024Test-Time Domain Generalization for Face Anti-Spoofingcited by 20
  5. 2022Cyclically Disentangled Feature Translation for Face Anti-spoofingcited by 10
  6. 2023Domain Generalization via Ensemble Stacking for Face Presentation Attack Detectioncited by 6
  7. 2025FaceShield: Explainable Face Anti-Spoofing with Multimodal Large Language Modelscited by 6
  8. 2022Generalized Face Anti-Spoofing via Multi-Task Learning and One-Side Meta Triplet Losscited by 5
  9. 2024Confidence Aware Learning for Reliable Face Anti-spoofingcited by 5
  10. 2025Harnessing Chain-of-Thought Reasoning in Multimodal Large Language Models for Face Anti-Spoofingcited by 5
  11. 2022Face Anti-Spoofing from the Perspective of Data Samplingcited by 4
  12. 2023Fine-Grained Annotation for Face Anti-Spoofingcited by 4
11 more
  1. 2024Generalized Face Liveness Detection via De-fake Face Generatorcited by 4
  2. 2023Deep Ensemble Learning with Frame Skipping for Face Anti-Spoofingcited by 3
  3. 2023Saliency-based Video Summarization for Face Anti-spoofingcited by 2
  4. 2023IFAST: Weakly Supervised Interpretable Face Anti-spoofing from Single-shot Binocular NIR Imagescited by 1
  5. 2026CPG-PAD: Concept-Informed Prompts Guided Presentation Attack Detectioncited by 1
  6. 2022Face Presentation Attack Detectioncited by 0
  7. 2023FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack Detectioncited by 0
  8. 2023Semi-Supervised learning for Face Anti-Spoofing using Apex framecited by 0
  9. 2024Advancing Cross-Domain Generalizability in Face Anti-Spoofing: Insights, Design, and Metricscited by 0
  10. 2025Generative Classifier for Domain Generalizationcited by 0
  11. 2025Steering Vision-Language Pre-trained Models for Incremental Face Presentation Attack Detectioncited by 0