mlsanityData to 7 Oct 2026

Face Anti-Spoofing Via Disentangled Representation Learning

arXiv 2008.08250 ↗First posted 19 Aug 2020cs.CVcited by 65

Not on the map. Why?

Abstract (arXiv)

Face anti-spoofing is crucial to security of face recognition systems. Previous approaches focus on developing discriminative models based on the features extracted from images, which may be still entangled between spoof patterns and real persons. In this paper, motivated by the disentangled representation learning, we propose a novel perspective of face anti-spoofing that disentangles the liveness features and content features from images, and the liveness features is further used for classification. We also put forward a Convolutional Neural Network (CNN) architecture with the process of disentanglement and combination of low-level and high-level supervision to improve the generalization capabilities. We evaluate our method on public benchmark datasets and extensive experimental results demonstrate the effectiveness of our method against the state-of-the-art competitors. Finally, we further visualize some results to help understand the effect and advantage of disentanglement.

Key facts. Cited by 65 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Aug 2020.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 18; 2022: 18; 2023: 15; 2024: 8; 2025: 5; 2026: 1.

65 papers.

Sort:

By area:

  1. 2023UCF: Uncovering Common Features for Generalizable Deepfake Detectioncited by 177
  2. 2022Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofingcited by 73
  3. 2024Detecting Multimedia Generated by Large AI Models: A Surveycited by 73
  4. 2024Preserving Fairness Generalization in Deepfake Detectioncited by 70
  5. 2022PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognitioncited by 67
  6. 2021Deep Learning for Face Anti-Spoofing: A Surveycited by 64
  7. 2021Adaptive Normalized Representation Learning for Generalizable Face Anti-Spoofingcited by 49
  8. 2021Dual-Cross Central Difference Network for Face Anti-Spoofingcited by 47
  9. 2021Dual Reweighting Domain Generalization for Face Presentation Attack Detectioncited by 47
  10. 2021Generalizable Representation Learning for Mixture Domain Face Anti-Spoofingcited by 46
  11. 2023FLIP: Cross-domain Face Anti-spoofing with Language Guidancecited by 45
  12. 2021Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detectioncited by 43
38 more
  1. 2023Instance-Aware Domain Generalization for Face Anti-Spoofingcited by 42
  2. 2024CFPL-FAS: Class Free Prompt Learning for Generalizable Face Anti-spoofingcited by 39
  3. 2022Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofingcited by 38
  4. 2022Exploring Disentangled Content Information for Face Forgery Detectioncited by 36
  5. 2021Meta-Teacher For Face Anti-Spoofingcited by 33
  6. 2022Generative Domain Adaptation for Face Anti-Spoofingcited by 33
  7. 2022Adaptive Mixture of Experts Learning for Generalizable Face Anti-Spoofingcited by 28
  8. 2022Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cuescited by 24
  9. 2021Feature Generation and Hypothesis Verification for Reliable Face Anti-Spoofingcited by 23
  10. 2023FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofingcited by 22
  11. 2021Dual Spoof Disentanglement Generation for Face Anti-spoofing with Depth Uncertainty Learningcited by 20
  12. 2024Test-Time Domain Generalization for Face Anti-Spoofingcited by 20
  13. 2021Structure Destruction and Content Combination for Face Anti-Spoofingcited by 18
  14. 20213D High-Fidelity Mask Face Presentation Attack Detection Challengecited by 18
  15. 2023MA-ViT: Modality-Agnostic Vision Transformers for Face Anti-Spoofingcited by 18
  16. 2022Digital and Physical Face Attacks: Reviewing and One Step Furthercited by 17
  17. 2022One-Class Knowledge Distillation for Face Presentation Attack Detectioncited by 12
  18. 2023Surveillance Face Anti-spoofingcited by 12
  19. 2023S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokenscited by 11
  20. 2021Disentangled Representation with Dual-stage Feature Learning for Face Anti-spoofingcited by 10
  21. 2021Consistency Regularization for Deep Face Anti-Spoofingcited by 10
  22. 2022Cyclically Disentangled Feature Translation for Face Anti-spoofingcited by 10
  23. 2021Federated Generalized Face Presentation Attack Detectioncited by 9
  24. 2023Visual Prompt Flexible-Modal Face Anti-Spoofingcited by 9
  25. 2022VLAD-VSA: Cross-Domain Face Presentation Attack Detection with Vocabulary Separation and Adaptationcited by 7
  26. 2025Domain Generalization for Face Anti-spoofing via Content-aware Composite Prompt Engineeringcited by 7
  27. 2023DSVAE: Interpretable Disentangled Representation for Synthetic Speech Detectioncited by 6
  28. 2024Generalized Face Anti-spoofing via Finer Domain Partition and Disentangling Liveness-irrelevant Factorscited by 6
  29. 2023Surveillance Face Presentation Attack Detection Challengecited by 5
  30. 2023Learning Disentangled Representation with Mutual Information Maximization for Real-Time UAV Trackingcited by 5
  31. 2025Benchmarking Unified Face Attack Detection via Hierarchical Prompt Tuningcited by 5
  32. 2021Asymmetric Modality Translation For Face Presentation Attack Detectioncited by 4
  33. 2023Fine-Grained Annotation for Face Anti-Spoofingcited by 4
  34. 2022Exposing Fine-Grained Adversarial Vulnerability of Face Anti-Spoofing Modelscited by 3
  35. 2022Learning Polysemantic Spoof Trace: A Multi-Modal Disentanglement Network for Face Anti-spoofingcited by 3
  36. 2024Unified Physical-Digital Attack Detection Challengecited by 3
  37. 2025FA^{3}-CLIP: Frequency-Aware Cues Fusion and Attack-Agnostic Prompt Learning for Unified Face Attack Detectioncited by 3
  38. 2021Domain Generalization with Pseudo-Domain Label for Face Anti-Spoofingcited by 2

50 most cited of 65 All 65 (JSON)