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This paper proposes a face anti-spoofing user-centered model (FAS-UCM). The major difficulty, in this case, is obtaining fraudulent images from all users to train the models. To overcome this problem, the proposed method is divided in three…

Computer Vision and Pattern Recognition · Computer Science 2019-07-18 Israel A. Laurensi R. , Luciana T. Menon , Manoel Camillo O. Penna N. , Alessandro L. Koerich , Alceu S. Britto

Face recognition technologies are increasingly used in various applications, yet they are vulnerable to face spoofing attacks. These spoofing attacks often involve unique 3D structures, such as printed papers or mobile device screens.…

Computer Vision and Pattern Recognition · Computer Science 2025-01-17 Ariel Larey , Eyal Rond , Omer Achrack

Active illumination is a prominent complement to enhance 2D face recognition and make it more robust, e.g., to spoofing attacks and low-light conditions. In the present work we show that it is possible to adopt active illumination to…

Computer Vision and Pattern Recognition · Computer Science 2020-04-08 J. Matias Di Martino , Fernando Suzacq , Mauricio Delbracio , Qiang Qiu , Guillermo Sapiro

Face anti-spoofing (FAS) plays a vital role in preventing face recognition (FR) systems from presentation attacks. Nowadays, FAS systems face the challenge of domain shift, impacting the generalization performance of existing FAS methods.…

Computer Vision and Pattern Recognition · Computer Science 2024-09-16 Xinxu Ge , Xin Liu , Zitong Yu , Jingang Shi , Chun Qi , Jie Li , Heikki Kälviäinen

Detecting manipulated facial images and videos is an increasingly important topic in digital media forensics. As advanced face synthesis and manipulation methods are made available, new types of fake face representations are being created…

Computer Vision and Pattern Recognition · Computer Science 2020-10-27 Hao Dang , Feng Liu , Joel Stehouwer , Xiaoming Liu , Anil Jain

Face anti-spoofing is crucial for the security of face recognition systems. Learning based methods especially deep learning based methods need large-scale training samples to reduce overfitting. However, acquiring spoof data is very…

Computer Vision and Pattern Recognition · Computer Science 2021-02-11 Jianzhu Guo , Xiangyu Zhu , Jinchuan Xiao , Zhen Lei , Genxun Wan , Stan Z. Li

Identity authentication is the process of verifying one's identity. There are several identity authentication methods, among which biometric authentication is of utmost importance. Facial recognition is a sort of biometric authentication…

Computer Vision and Pattern Recognition · Computer Science 2022-12-15 Matineh Pooshideh

Manipulated videos, especially those where the identity of an individual has been modified using deep neural networks, are becoming an increasingly relevant threat in the modern day. In this paper, we seek to develop a generalizable,…

Computer Vision and Pattern Recognition · Computer Science 2021-09-23 Steven Schwarcz , Rama Chellappa

Face anti-spoofing is crucial to the security of face recognition systems. Most previous methods formulate face anti-spoofing as a supervised learning problem to detect various predefined presentation attacks, which need large scale…

Computer Vision and Pattern Recognition · Computer Science 2021-09-08 Yunxiao Qin , Chenxu Zhao , Xiangyu Zhu , Zezheng Wang , Zitong Yu , Tianyu Fu , Feng Zhou , Jingping Shi , Zhen Lei

Data poisoning has been proposed as a compelling defense against facial recognition models trained on Web-scraped pictures. Users can perturb images they post online, so that models will misclassify future (unperturbed) pictures. We…

Machine Learning · Computer Science 2022-03-15 Evani Radiya-Dixit , Sanghyun Hong , Nicholas Carlini , Florian Tramèr

A face spoofing attack occurs when an intruder attempts to impersonate someone who carries a gainful authentication clearance. It is a trending topic due to the increasing demand for biometric authentication on mobile devices, high-security…

Computer Vision and Pattern Recognition · Computer Science 2023-08-25 Rafael Henrique Vareto , Araceli Marcia Sandanha , William Robson Schwartz

Face authentication systems are becoming increasingly prevalent, especially with the rapid development of Deep Learning technologies. However, human facial information is easy to be captured and reproduced, which makes face authentication…

Computer Vision and Pattern Recognition · Computer Science 2018-08-23 Di Tang , Zhe Zhou , Yinqian Zhang , Kehuan Zhang

With diverse presentation forgery methods emerging continually, detecting the authenticity of images has drawn growing attention. Although existing methods have achieved impressive accuracy in training dataset detection, they still perform…

Computer Vision and Pattern Recognition · Computer Science 2024-03-20 Yingxin Lai , Guoqing Yang Yifan He , Zhiming Luo , Shaozi Li

The unprecedented capture and application of face images raise increasing concerns on anonymization to fight against privacy disclosure. Most existing methods may suffer from the problem of excessive change of the identity-independent…

Computer Vision and Pattern Recognition · Computer Science 2024-07-09 Zhenzhong Kuang , Xiaochen Yang , Yingjie Shen , Chao Hu , Jun Yu

In videos containing spoofed faces, we may uncover the spoofing evidence based on either photometric or dynamic abnormality, even a combination of both. Prevailing face anti-spoofing (FAS) approaches generally concentrate on the…

Computer Vision and Pattern Recognition · Computer Science 2025-02-25 Jingyi Yang , Zitong Yu , Xiuming Ni , Jia He , Hui Li

Typical fingerprint recognition systems are comprised of a spoof detection module and a subsequent recognition module, running one after the other. In this paper, we reformulate the workings of a typical fingerprint recognition system. In…

Computer Vision and Pattern Recognition · Computer Science 2021-07-26 Additya Popli , Saraansh Tandon , Joshua J. Engelsma , Naoyuki Onoe , Atsushi Okubo , Anoop Namboodiri

Generalizability to unseen forgery types is crucial for face forgery detectors. Recent works have made significant progress in terms of generalization by synthetic forgery data augmentation. In this work, we explore another path for…

Computer Vision and Pattern Recognition · Computer Science 2024-11-19 Jianwei Fei , Yunshu Dai , Huaming Wang , Zhihua Xia

Recent research on biometrics focuses on achieving a high success rate of authentication and addressing the concern of various spoofing attacks. Although hand geometry recognition provides adequate security over unauthorized access, it is…

Computer Vision and Pattern Recognition · Computer Science 2021-10-26 Asish Bera , Ratnadeep Dey , Debotosh Bhattacharjee , Mita Nasipuri , Hubert P. H. Shum

Real-world face recognition systems are vulnerable to both physical presentation attacks (PAs) and digital forgery attacks (DFs). We aim to achieve comprehensive protection of biometric data by implementing a unified physical-digital…

Computer Vision and Pattern Recognition · Computer Science 2025-12-09 Jiabao Guo , Yadian Wang , Hui Ma , Yuhao Fu , Ju Jia , Hui Liu , Shengeng Tang , Lechao Cheng , Yunfeng Diao , Ajian Liu

We assess the vulnerabilities of deep face recognition systems for images that falsify/spoof multiple identities simultaneously. We demonstrate that, by manipulating the deep feature representation extracted from a face image via…

Computer Vision and Pattern Recognition · Computer Science 2021-10-05 Takuma Amada , Seng Pei Liew , Kazuya Kakizaki , Toshinori Araki
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