Domain-generalizable Face Anti-Spoofing with Patch-based Multi-tasking and Artifact Pattern Conversion
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Abstract (arXiv)
Face Anti-Spoofing (FAS) algorithms, designed to secure face recognition systems against spoofing, struggle with limited dataset diversity, impairing their ability to handle unseen visual domains and spoofing methods. We introduce the Pattern Conversion Generative Adversarial Network (PCGAN) to enhance domain generalization in FAS. PCGAN effectively disentangles latent vectors for spoof artifacts and facial features, allowing to generate images with diverse artifacts. We further incorporate patch-based and multi-task learning to tackle partial attacks and overfitting issues to facial features. Our extensive experiments validate PCGAN's effectiveness in domain generalization and detecting partial attacks, giving a substantial improvement in facial recognition security.
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References · 31
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- 2020Swapping Autoencoder for Deep Image Manipulationcited by 215
- 2019Biometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Networkcited by 78
- 2022Domain Generalization via Shuffled Style Assembly for Face Anti-Spoofingcited by 73
- 2022PatchNet: A Simple Face Anti-Spoofing Framework via Fine-Grained Patch Recognitioncited by 67
- 2020CASIA-SURF CeFA: A Benchmark for Multi-modal Cross-ethnicity Face Anti-spoofingcited by 66
- 2019CASIA-SURF: A Large-scale Multi-modal Benchmark for Face Anti-spoofingcited by 61
19 more
- 2023Rethinking Domain Generalization for Face Anti-spoofing: Separability and Alignmentcited by 47
- 2023FLIP: Cross-domain Face Anti-spoofing with Language Guidancecited by 45
- 2022Multi-domain Learning for Updating Face Anti-spoofing Modelscited by 39
- 2024CFPL-FAS: Class Free Prompt Learning for Generalizable Face Anti-spoofingcited by 39
- 2022Generative Domain Adaptation for Face Anti-Spoofingcited by 33
- 2024FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learningcited by 21
- 2023Rethinking Vision Transformer and Masked Autoencoder in Multimodal Face Anti-Spoofingcited by 19
- 2021Structure Destruction and Content Combination for Face Anti-Spoofingcited by 18
- 2020CIT-GAN: Cyclic Image Translation Generative Adversarial Network With Application in Iris Presentation Attack Detectioncited by 16
- 2024Towards Data-Centric Face Anti-Spoofing: Improving Cross-domain Generalization via Physics-based Data Synthesiscited by 16
- 2019Domain Adaptation in Multi-Channel Autoencoder based Features for Robust Face Anti-Spoofingcited by 12
- 2021Consistency Regularization for Deep Face Anti-Spoofingcited by 10
- 2020PipeNet: Selective Modal Pipeline of Fusion Network for Multi-Modal Face Anti-Spoofingcited by 7
- 2025Domain Generalization for Face Anti-spoofing via Content-aware Composite Prompt Engineeringcited by 7
- 2022Generalized Face Anti-Spoofing via Multi-Task Learning and One-Side Meta Triplet Losscited by 5
- 2024Confidence Aware Learning for Reliable Face Anti-spoofingcited by 5
- 2024Generalized Face Liveness Detection via De-fake Face Generatorcited by 4
- 2019Style Transfer Applied to Face Liveness Detection with User-Centered Modelscited by 3
- 2025Learning Knowledge-based Prompts for Robust 3D Mask Presentation Attack Detectioncited by 2
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