Results 31 to 40 of about 504 (172)

Generative Domain Adaptation for Face Anti-Spoofing

, 2022
Face anti-spoofing (FAS) approaches based on unsupervised domain adaption (UDA) have drawn growing attention due to promising performances for target scenarios. Most existing UDA FAS methods typically fit the trained models to the target domain via aligning the distribution of semantic high-level features. However, insufficient supervision of unlabeled
Qianyu Zhou 0001, Ke-Yue Zhang, Taiping Yao, Ran Yi 0002, Kekai Sheng, Shouhong Ding, Lizhuang Ma   +6 more
openaire   +2 more sources

Self-Domain Adaptation for Face Anti-Spoofing

Proceedings of the AAAI Conference on Artificial Intelligence, 2021
Although current face anti-spoofing methods achieve promising results under intra-dataset testing, they suffer from poor generalization to unseen attacks. Most existing works adopt domain adaptation (DA) or domain generalization (DG) techniques to address this problem.
Jingjing Wang 0005, Jingyi Zhang 0003, Ying Bian, Youyi Cai, Chunmao Wang, Shiliang Pu   +5 more
openaire   +2 more sources

Consistency Regularization for Deep Face Anti-Spoofing

CoRR, 2021
Face anti-spoofing (FAS) plays a crucial role in securing face recognition systems. Empirically, given an image, a model with more consistent output on different views of this image usually performs better, as shown in Fig.1. Motivated by this exciting observation, we conjecture that encouraging feature consistency of different views may be a promising
Zezheng Wang, Zitong Yu, Xun Wang, Yunxiao Qin, Jiahong Li, Chenxu Zhao, Zhen Lei 0001, Xin Liu 0012, Size Li, Zhongyuan Wang 0006   +9 more
openaire   +2 more sources

Fine-Grained Annotation for Face Anti-Spoofing

CoRR, 2023
Face anti-spoofing plays a critical role in safeguarding facial recognition systems against presentation attacks. While existing deep learning methods show promising results, they still suffer from the lack of fine-grained annotations, which lead models to learn task-irrelevant or unfaithful features. In this paper, we propose a fine-grained annotation
Xu Chen, Yunde Jia, Yuwei Wu 0001
openaire   +2 more sources

Face anti‐spoofing with refined triplet loss and multi‐level attention constraint network

Electronics Letters, 2021
One critical issue for existing face recognition (FR) systems is to ensure its accuracy and robustness, which calls for the development of face anti‐spoofing (FAS) algorithms to work against presentation attacks (PA).
Xingzhong Nong, Ying Zeng, Haifeng Hu
doaj   +1 more source

A Novel Feature Descriptor for Face Anti-Spoofing Using Texture Based Method

Cybernetics and Information Technologies, 2020
In this paper we propose a novel approach for face anti-spoofing called Extended Division Directional Ternary Co-relation Pattern (EDDTCP). The EDDTCP encodes co-relation of ternary edges based on the centre pixel gray values with its immediate ...
Raghavendra R. J., Kunte R. Sanjeev
doaj   +1 more source

A Face Spoofing Detection Method Based on Domain Adaptation and Lossless Size Adaptation

IEEE Access, 2020
In this paper, a face spoofing detection method called the Fully Convolutional Network with Domain Adaptation and Lossless Size Adaptation (FCN-DA-LSA) is proposed.
Wenyun Sun, Yu Song, Haitao Zhao, Zhong Jin   +3 more
doaj   +1 more source

Suppressing Spoof-Irrelevant Factors for Domain-Agnostic Face Anti-Spoofing

IEEE Access, 2021
Face anti-spoofing aims to prevent false authentications of face recognition systems by distinguishing whether an image is originated from a human face or a spoof medium.
Taewook Kim, Yonghyun Kim
doaj   +1 more source

Surveillance Face Anti-Spoofing

IEEE Transactions on Information Forensics and Security
Face Anti-spoofing (FAS) is essential to secure face recognition systems from various physical attacks. However, recent research generally focuses on short-distance applications (i.e., phone unlocking) while lacking consideration of long-distance scenes (i.e., surveillance security checks). In order to promote relevant research and fill this gap in the
Hao Fang, Ajian Liu, Jun Wan, Sergio Escalera, Chenxu Zhao, Xu Zhang, Stan Z. Li, Zhen Lei   +7 more
openaire   +3 more sources

A Real-Time Face Detection Method Based on Blink Detection

IEEE Access, 2023
Face anti-spoofing refers to the computer determining whether the face detected is a real face or a forged face. In user authentication scenarios, photo fraud attacks are easy to occur, where an illegal user logs into the system using a legitimate user ...
Hui Qi, Chenxu Wu, Ying Shi, Xiaobo Qi, Kaige Duan, Xiaobin Wang   +5 more
doaj   +1 more source