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Anomaly detection-based spoof attack detection is a recent development in face Presentation Attack Detection (fPAD), where a spoof detector is learned using only non-attacked images of users.
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B. Schölkopf, J. C. Platt, J. Shawe-Taylor, A. J. Smola, and R. C. Williamson · 2001
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Distinctive image features from scale-invariant keypoints
D. G. Lowe · 2004
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Support vector data description
D. M. Tax and R. P. Duin · 2004
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Histograms of oriented gradients for human detection
N. Dalal and B. Triggs · 2005
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Face description with local binary patterns: Application to face recognition
T. Ahonen, A. Hadid, and M. Pietikainen · 2006
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Surf: Speeded up robust features
H. Bay, T. Tuytelaars, and L. Van Gool · 2006
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C.-C. Chang and C.-J. Lin · 2011
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Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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On the effectiveness of local binary patterns in face anti-spoofing
I. Chingovska, A. Anjos, and S. Marcel · 2012
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Image quality assessment for fake biometric detection: Application to iris, fingerprint, and face recognition
J. Galbally, S. Marcel, and J. Fierrez · 2013
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Face anti-spoofing based on general image quality assessment
J. Galbally and S. Marcel · 2014
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Handbook of biometric anti-spoofing
S. Marcel, M. S. Nixon, and S. Z. Li · 2014
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Face anti-spoofing based on color texture analysis
Z. Boulkenafet, J. Komulainen, and A. Hadid · 2015
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Deep face recognition
O. M. Parkhi, A. Vedaldi, and A. Zisserman · 2015
Cited alongside, same era.
Face antispoofing using speeded-up robust features and fisher vector encoding
Z. Boulkenafet, J. Komulainen, and A. Hadid · 2016
Cited alongside, same era.
3d mask face anti-spoofing with remote photoplethysmography
S. Liu, P. C. Yuen, S. Zhang, and G. Zhao · 2016
Cited alongside, same era.
Sparse representation-based open set recognition
H. Zhang and V. M. Patel · 2016
Cited alongside, same era.
An anomaly detection approach to face spoofing detection: A new formulation and evaluation protocol
S. R. Arashloo, J. Kittler, and W. Christmas · 2017
Cited alongside, same era.
Face anti-spoofing using patch and depth-based cnns
Y. Atoum, Y. Liu, A. Jourabloo, and X. Liu · 2017
Cited alongside, same era.
One-class convolutional neural network
P. Oza and V. M. Patel · 2018
Later among the works it cites.
Dual-minimax probability machines for one-class mobile active authentication
P. Perera and V. M. Patel · 2018
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Unknown presentation attack detection with face rgb images
F. Xiong and W. AbdAlmageed · 2018
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Spoofing attack detection by anomaly detection
S. Fatemifar, S. R. Arashloo, M. Awais, and J. Kittler · 2019
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Combining multiple one-class classifiers for anomaly based face spoofing attack detection
S. Fatemifar, M. Awais, S. R. Arashloo, and J. Kittler · 2019
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Biometric face presentation attack detection with multi-channel convolutional neural network
A. George, Z. Mostaani, D. Geissenbuhler, O. Nikisins, A. Anjos, and S. Marcel · 2019
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OULU-NPU: A mobile face presentation attack database with real-world variations
Z. Boulkenafet, J. Komulainen, L. Li, X. Feng, and A. Hadid · 2017
Cited alongside, same era.
Presentation attack detection methods for face recognition systems: A comprehensive survey
R. Ramachandra and C. Busch · 2017
Cited alongside, same era.
Pairwise confusion for fine-grained visual classification
A. Dubey, O. Gupta, P. Guo, R. Raskar, R. Farrell, and N. Naik · 2018
Cited alongside, same era.
Unsupervised domain adaptation for face anti-spoofing
H. Li, W. Li, H. Cao, S. Wang, F. Huang, and A. C. Kot · 2018
Cited alongside, same era.
Remote photoplethysmography correspondence feature for 3d mask face presentation attack detection
S.-Q. Liu, X. Lan, and P. C. Yuen · 2018
Cited alongside, same era.
Learning deep models for face anti-spoofing: Binary or auxiliary supervision
Y. Liu, A. Jourabloo, and X. Liu · 2018
Cited alongside, same era.
Later among the works it cites.
Active authentication using an autoencoder regularized cnn-based one-class classifier
P. Oza and V. M. Patel · 2019
Later among the works it cites.
Deep transfer learning for multiple class novelty detection
P. Perera and V. M. Patel · 2019
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Learning deep features for one-class classification
P. Perera and V. M. Patel · 2019
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Multiple class novelty detection under data distribution shift
P. Oza, H. Nguyen, and V. M. Patel · 2020
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Utilizing patch-level activity patterns for multiple class novelty detection
P. Oza and V. M. Patel · 2020
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Generative-discriminative feature representations for open-set recognition
P. Perera, V. I. Morariu, R. Jain, V. Manjunatha, C. Wigington, V. Ordonez, and V. M. Patel · 2020
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Open-set adversarial defense
R. Shao, P. Perera, P. Yuen, and V. M. Patel · 2020
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