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Recently, vision transformer (ViT) based multimodal learning methods have been proposed to improve the robustness of face anti-spoofing (FAS) systems.
Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
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Jukka Komulainen, Abdenour Hadid, and Matti Pietikainen · 2013
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Iso/iec jtc 1/sc 37 biometrics: Information technology biometric presentation attack detection part 1: Framework
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Secure face unlock: Spoof detection on smartphones
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Face antispoofing using speeded-up robust features and fisher vector encoding
Zinelabidine Boulkenafet, Jukka Komulainen, and Abdenour Hadid · 2017
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3d convolutional neural network based on face anti-spoofing
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Learning deep models for face anti-spoofing: Binary or auxiliary supervision
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Deep pixel-wise binary supervision for face presentation attack detection
Anjith George and Sébastien Marcel · 2019
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Biometric face presentation attack detection with multi-channel convolutional neural network
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Face anti-spoofing via deep local binary pattern
Lei Li and Xiaoyi Feng · 2019
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Domain adaptation in multi-channel autoencoder based features for robust face anti-spoofing
Olegs Nikisins, Anjith George, and Sébastien Marcel · 2019
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Facebagnet: Bag-of-local-features model for multi-modal face anti-spoofing
Tao Shen, Yuyu Huang, and Zhijun Tong · 2019
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Face anti-spoofing: Model matters, so does data
Xiao Yang, Wenhan Luo, Linchao Bao, Yuan Gao, Dihong Gong, Shibao Zheng, Zhifeng Li, and Wei Liu · 2019
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Feathernets: Convolutional neural networks as light as feather for face anti-spoofing
Peng Zhang, Fuhao Zou, Zhiwen Wu, Nengli Dai, Skarpness Mark, Michael Fu, Juan Zhao, and Kai Li · 2019
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A dataset and benchmark for large-scale multi-modal face anti-spoofing
Shifeng Zhang, Xiaobo Wang, Ajian Liu, Chenxu Zhao, Jun Wan, Sergio Escalera, Hailin Shi, Zezheng Wang, and Stan Z Li · 2019
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Learning one class representations for face presentation attack detection using multi-channel convolutional neural networks
Anjith George and Sébastien Marcel · 2020
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Early convolutions help transformers see better
Tete Xiao, Mannat Singh, Eric Mintun, Trevor Darrell, Piotr Dollár, and Ross Girshick · 2021
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Transrppg: Remote photoplethysmography transformer for 3d mask face presentation attack detection
Zitong Yu, Xiaobai Li, Pichao Wang, and Guoying Zhao · 2021
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Dual-cross central difference network for face anti-spoofing
Zitong Yu, Yunxiao Qin, Hengshuang Zhao, Xiaobai Li, and Guoying Zhao · 2021
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On the effectiveness of vision transformers for zero-shot face anti-spoofing
Anjith George and Sebastien Marcel · 2020
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Learning meta model for zero-and few-shot face anti-spoofing
Yunxiao Qin, Chenxu Zhao, Xiangyu Zhu, Zezheng Wang, Zitong Yu, Tianyu Fu, Feng Zhou, Jingping Shi, and Zhen Lei · 2020
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Face anti-spoofing with human material perception
Zitong Yu, Xiaobai Li, Xuesong Niu, Jingang Shi, and Guoying Zhao · 2020
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Multi-modal face anti-spoofing based on central difference networks
Zitong Yu, Yunxiao Qin, Xiaobai Li, Zezheng Wang, Chenxu Zhao, Zhen Lei, and Guoying Zhao · 2020
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Searching central difference convolutional networks for face anti-spoofing
Zitong Yu, Chenxu Zhao, Zezheng Wang, Yunxiao Qin, Zhuo Su, Xiaobai Li, Feng Zhou, and Guoying Zhao · 2020
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Casia-surf: A large-scale multi-modal benchmark for face anti-spoofing
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Vatt: Transformers for multimodal self-supervised learning from raw video, audio and text
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Adaptive transformers for robust few-shot cross-domain face anti-spoofing
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Contrastive context-aware learning for 3d high-fidelity mask face presentation attack detection
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Vitranspad: Video transformer using convolution and self-attention for face presentation attack detection
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Self-supervised 2d face presentation attack detection via temporal sequence sampling
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Conv-mlp: A convolution and mlp mixed model for multimodal face anti-spoofing
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Face anti-spoofing using transformers with relation-aware mechanism
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Learning multi-granularity temporal characteristics for face anti-spoofing
Zhuo Wang, Qiangchang Wang, Weihong Deng, and Guodong Guo · 2022
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Physformer: facial video-based physiological measurement with temporal difference transformer
Zitong Yu, Yuming Shen, Jingang Shi, Hengshuang Zhao, Philip HS Torr, and Guoying Zhao · 2022
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i-mae: Are latent representations in masked autoencoders linearly separable?
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Learning to prompt for vision-language models
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