mlsanityData to 7 Oct 2026

Contrastive Context-Aware Learning for 3D High-Fidelity Mask Face Presentation Attack Detection

arXiv 2104.06148 ↗First posted 13 Apr 2021cs.CVcited by 43

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Abstract (arXiv)

Face presentation attack detection (PAD) is essential to secure face recognition systems primarily from high-fidelity mask attacks. Most existing 3D mask PAD benchmarks suffer from several drawbacks: 1) a limited number of mask identities, types of sensors, and a total number of videos; 2) low-fidelity quality of facial masks. Basic deep models and remote photoplethysmography (rPPG) methods achieved acceptable performance on these benchmarks but still far from the needs of practical scenarios. To bridge the gap to real-world applications, we introduce a largescale High-Fidelity Mask dataset, namely CASIA-SURF HiFiMask (briefly HiFiMask). Specifically, a total amount of 54,600 videos are recorded from 75 subjects with 225 realistic masks by 7 new kinds of sensors. Together with the dataset, we propose a novel Contrastive Context-aware Learning framework, namely CCL. CCL is a new training methodology for supervised PAD tasks, which is able to learn by leveraging rich contexts accurately (e.g., subjects, mask material and lighting) among pairs of live faces and high-fidelity mask attacks. Extensive experimental evaluations on HiFiMask and three additional 3D mask datasets demonstrate the effectiveness of our method.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 30 of its 59 references that are in the map. First posted on arXiv 13 Apr 2021.

Builds on

30 of 59 references.

References · 30

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2020An Image is Worth 16x16 Words: Transformers for Image Recognition at Scalecited by 29,915
  3. 2020A Simple Framework for Contrastive Learning of Visual Representationscited by 11,979
  4. 2019Momentum Contrast for Unsupervised Visual Representation Learningcited by 7,482
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  6. 2020Bootstrap your own latent: A new approach to self-supervised Learningcited by 4,712
  7. 2020Exploring Simple Siamese Representation Learningcited by 2,853
  8. 2020Supervised Contrastive Learningcited by 2,803
  9. 2020Searching Central Difference Convolutional Networks for Face Anti-Spoofingcited by 173
  10. 2018Learning Deep Models for Face Anti-Spoofing: Binary or Auxiliary Supervisioncited by 167
  11. 2019Attention-based Dropout Layer for Weakly Supervised Object Localizationcited by 125
  12. 2020CelebA-Spoof: Large-Scale Face Anti-Spoofing Dataset with Rich Annotationscited by 109
18 more
  1. 2020NAS-FAS: Static-Dynamic Central Difference Network Search for Face Anti-Spoofingcited by 104
  2. 2014Learn Convolutional Neural Network for Face Anti-Spoofingcited by 80
  3. 2019Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Networkcited by 78
  4. 2019Deep Pixel-wise Binary Supervision for Face Presentation Attack Detectioncited by 76
  5. 2019Deep Tree Learning for Zero-shot Face Anti-Spoofingcited by 73
  6. 2020CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofingcited by 66
  7. 2020Face Anti-Spoofing Via Disentangled Representation Learningcited by 65
  8. 2020Face Anti-Spoofing with Human Material Perceptioncited by 62
  9. 2020On Disentangling Spoof Trace for Generic Face Anti-Spoofingcited by 62
  10. 2018A Dataset and Benchmark for Large-scale Multi-modal Face Anti-spoofingcited by 51
  11. 2021FaceX-Zoo: A PyTorch Toolbox for Face Recognitioncited by 49
  12. 2019Learning Meta Model for Zero- and Few-shot Face Anti-spoofingcited by 44
  13. 2016Learning Deep Feature Representations with Domain Guided Dropout for Person Re-identificationcited by 41
  14. 2021Cross Modal Focal Loss for RGBD Face Anti-Spoofingcited by 41
  15. 2020Learning One Class Representations for Face Presentation Attack Detection using Multi-channel Convolutional Neural Networkscited by 36
  16. 2020Deep Models and Shortwave Infrared Information to Detect Face Presentation Attackscited by 29
  17. 20203D Face Anti-spoofing with Factorized Bilinear Codingcited by 20
  18. 2019Face Liveness Detection Based on Client Identity Using Siamese Networkcited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 4; 2022: 6; 2023: 14; 2024: 8; 2025: 10; 2026: 1.

43 papers.

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  1. 2022Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofingcited by 73
  2. 2021Deep Learning for Face Anti-Spoofing: A Surveycited by 64
  3. 2024CFPL-FAS: Class Free Prompt Learning for Generalizable Face Anti-spoofingcited by 39
  4. 2022Benchmarking Joint Face Spoofing and Forgery Detection with Visual and Physiological Cuescited by 24
  5. 2023FM-ViT: Flexible Modal Vision Transformers for Face Anti-Spoofingcited by 22
  6. 2022Flexible-Modal Face Anti-Spoofing: A Benchmarkcited by 20
  7. 2023Rethinking Vision Transformer and Masked Autoencoder in Multimodal Face Anti-Spoofingcited by 19
  8. 20213D High-Fidelity Mask Face Presentation Attack Detection Challengecited by 18
  9. 2023MA-ViT: Modality-Agnostic Vision Transformers for Face Anti-Spoofingcited by 18
  10. 2022Digital and Physical Face Attacks: Reviewing and One Step Furthercited by 17
  11. 2023SynthASpoof: Developing Face Presentation Attack Detection Based on Privacy-friendly Synthetic Datacited by 17
  12. 2024Unified Physical-Digital Face Attack Detectioncited by 17
31 more
  1. 2024Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data Synthesiscited by 16
  2. 2023Unified Frequency-Assisted Transformer Framework for Detecting and Grounding Multi-Modal Manipulationcited by 14
  3. 2023Surveillance Face Anti-spoofingcited by 12
  4. 2023Rehearsal-Free Domain Continual Face Anti-Spoofing: Generalize More and Forget Lesscited by 12
  5. 2023S-Adapter: Generalizing Vision Transformer for Face Anti-Spoofing with Statistical Tokenscited by 11
  6. 2021Consistency Regularization for Deep Face Anti-Spoofingcited by 10
  7. 2024Joint Physical-Digital Facial Attack Detection Via Simulating Spoofing Cluescited by 8
  8. 2024La-SoftMoE CLIP for Unified Physical-Digital Face Attack Detectioncited by 8
  9. 2024DiffFAS: Face Anti-Spoofing via Generative Diffusion Modelscited by 7
  10. 2025Domain Generalization for Face Anti-spoofing via Content-aware Composite Prompt Engineeringcited by 7
  11. 2023Surveillance Face Presentation Attack Detection Challengecited by 5
  12. 2025Benchmarking Unified Face Attack Detection via Hierarchical Prompt Tuningcited by 5
  13. 2025Harnessing Chain-of-Thought Reasoning in Multimodal Large Language Models for Face Anti-Spoofingcited by 5
  14. 2024Unified Physical-Digital Attack Detection Challengecited by 3
  15. 2025FA^{3}-CLIP: Frequency-Aware Cues Fusion and Attack-Agnostic Prompt Learning for Unified Face Attack Detectioncited by 3
  16. 2023Wild Face Anti-Spoofing Challenge 2023: Benchmark and Resultscited by 2
  17. 2023TeG-DG: Textually Guided Domain Generalization for Face Anti-Spoofingcited by 2
  18. 2025SUEDE:Shared Unified Experts for Physical-Digital Face Attack Detection Enhancementcited by 2
  19. 2025Learning Knowledge-based Prompts for Robust 3D Mask Presentation Attack Detectioncited by 2
  20. 2021Deep Learning meets Liveness Detection: Recent Advancements and Challengescited by 1
  21. 2022Image Harmonization with Region-wise Contrastive Learningcited by 1
  22. 2023Mask Attack Detection Using Vascular-weighted Motion-robust rPPG Signalscited by 1
  23. 2023Hyperbolic Face Anti-Spoofingcited by 1
  24. 2023Flow-Attention-based Spatio-Temporal Aggregation Network for 3D Mask Detectioncited by 1
  25. 2025Optimizing DINOv2 with Registers for Face Anti-Spoofingcited by 1
  26. 2026CPG-PAD: Concept-Informed Prompts Guided Presentation Attack Detectioncited by 1
  27. 2022Face Presentation Attack Detectioncited by 0
  28. 2024VoxAtnNet: A 3D Point Clouds Convolutional Neural Network for Generalizable Face Presentation Attack Detectioncited by 0
  29. 2025Unified Face Matching and Physical-Digital Spoofing Attack Detectioncited by 0
  30. 2025In-context Learning of Vision Language Models for Detection of Physical and Digital Attacks against Face Recognition Systemscited by 0
  31. 2025Spoofing-aware Prompt Learning for Unified Physical-Digital Facial Attack Detectioncited by 0