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Biometrics systems have significantly improved person identification and authentication, playing an important role in personal, national, and global security. However, these systems might be deceived (or "spoofed") and, despite the recent…

Computer Vision and Pattern Recognition · Computer Science 2016-11-17 David Menotti , Giovani Chiachia , Allan Pinto , William Robson Schwartz , Helio Pedrini , Alexandre Xavier Falcao , Anderson Rocha

Face morphing, a sophisticated presentation attack technique, poses significant security risks to face recognition systems. Traditional methods struggle to detect morphing attacks, which involve blending multiple face images to create a…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Iurii Medvedev , Joana Pimenta , Nuno Gonçalves

State-of-the-art defense mechanisms against face attacks achieve near perfect accuracies within one of three attack categories, namely adversarial, digital manipulation, or physical spoofs, however, they fail to generalize well when tested…

Computer Vision and Pattern Recognition · Computer Science 2021-04-07 Debayan Deb , Xiaoming Liu , Anil K. Jain

As face recognition is widely used in diverse security-critical applications, the study of face anti-spoofing (FAS) has attracted more and more attention. Several FAS methods have achieved promising performances if the attack types in the…

Computer Vision and Pattern Recognition · Computer Science 2021-10-19 Yu-Chun Wang , Chien-Yi Wang , Shang-Hong Lai

The surge in face forgeries has increasingly undermined confidence in the authenticity of online content. As generation algorithms rapidly evolve, new fake categories will constantly emerge, severely challenging existing face forgery…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Zhongyi Cai , Bryce Gernon , Wentao Bao , Yifan Li , Matthew Wright , Yu Kong

Face anti-spoofing (FAS) is crucial for protecting facial recognition systems from presentation attacks. Previous methods approached this task as a classification problem, lacking interpretability and reasoning behind the predicted results.…

Computer Vision and Pattern Recognition · Computer Science 2025-11-18 Hongyang Wang , Yichen Shi , Zhuofu Tao , Yuhao Gao , Liepiao Zhang , Xun Lin , Jun Feng , Xiaochen Yuan , Zitong Yu , Xiaochun Cao

Face anti-spoofing is crucial to security of face recognition systems. Previous approaches focus on developing discriminative models based on the features extracted from images, which may be still entangled between spoof patterns and real…

Computer Vision and Pattern Recognition · Computer Science 2020-08-20 Ke-Yue Zhang , Taiping Yao , Jian Zhang , Ying Tai , Shouhong Ding , Jilin Li , Feiyue Huang , Haichuan Song , Lizhuang Ma

Ensuring the reliability of face recognition systems against presentation attacks necessitates the deployment of face anti-spoofing techniques. Despite considerable advancements in this domain, the ability of even the most state-of-the-art…

Computer Vision and Pattern Recognition · Computer Science 2024-04-26 Jiawei Chen , Xiao Yang , Heng Yin , Mingzhi Ma , Bihui Chen , Jianteng Peng , Yandong Guo , Zhaoxia Yin , Hang Su

Face recognition technology has dramatically transformed the landscape of security, surveillance, and authentication systems, offering a user-friendly and non-invasive biometric solution. However, despite its significant advantages, face…

Computer Vision and Pattern Recognition · Computer Science 2025-07-04 Arun Kunwar , Ajita Rattani

The vulnerability against presentation attacks is a crucial problem undermining the wide-deployment of face recognition systems. Though presentation attack detection (PAD) systems try to address this problem, the lack of generalization and…

Computer Vision and Pattern Recognition · Computer Science 2022-02-22 Anjith George , David Geissbuhler , Sebastien Marcel

Face anti-spoofing is crucial for ensuring the security and reliability of face recognition systems. Several existing face anti-spoofing methods utilize GAN-like networks to detect presentation attacks by estimating the noise pattern of a…

Computer Vision and Pattern Recognition · Computer Science 2024-01-17 Bin Zhang , Xiangyu Zhu , Xiaoyu Zhang , Zhen Lei

Face recognition systems are frequently subjected to a variety of physical and digital attacks of different types. Previous methods have achieved satisfactory performance in scenarios that address physical attacks and digital attacks,…

Computer Vision and Pattern Recognition · Computer Science 2024-04-15 Xianhua He , Dashuang Liang , Song Yang , Zhanlong Hao , Hui Ma , Binjie Mao , Xi Li , Yao Wang , Pengfei Yan , Ajian Liu

Face recognition technology has been widely used in daily interactive applications such as checking-in and mobile payment due to its convenience and high accuracy. However, its vulnerability to presentation attacks (PAs) limits its reliable…

Computer Vision and Pattern Recognition · Computer Science 2022-12-08 Zitong Yu , Chenxu Zhao , Zhen Lei

Prior studies show that the key to face anti-spoofing lies in the subtle image pattern, termed "spoof trace", e.g., color distortion, 3D mask edge, Moire pattern, and many others. Designing a generic anti-spoofing model to estimate those…

Computer Vision and Pattern Recognition · Computer Science 2020-07-21 Yaojie Liu , Joel Stehouwer , Xiaoming Liu

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

Face anti-spoofing is significant to the security of face recognition systems. Previous works on depth supervised learning have proved the effectiveness for face anti-spoofing. Nevertheless, they only considered the depth as an auxiliary…

Computer Vision and Pattern Recognition · Computer Science 2019-03-06 Zezheng Wang , Chenxu Zhao , Yunxiao Qin , Qiusheng Zhou , Guojun Qi , Jun Wan , Zhen Lei

Face anti-spoofing (a.k.a presentation attack detection) has drawn growing attention due to the high-security demand in face authentication systems. Existing CNN-based approaches usually well recognize the spoofing faces when training and…

Computer Vision and Pattern Recognition · Computer Science 2019-01-18 Xiaoguang Tu , Jian Zhao , Mei Xie , Guodong Du , Hengsheng Zhang , Jianshu Li , Zheng Ma , Jiashi Feng

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

DeepFakes have raised serious societal concerns, leading to a great surge in detection-based forensics methods in recent years. Face forgery recognition is a standard detection method that usually follows a two-phase pipeline. While those…

Computer Vision and Pattern Recognition · Computer Science 2024-05-27 Cong Zhang , Honggang Qi , Shuhui Wang , Yuezun Li , Siwei Lyu

Automatic methods for detecting presentation attacks are essential to ensure the reliable use of facial recognition technology. Most of the methods available in the literature for presentation attack detection (PAD) fails in generalizing to…

Computer Vision and Pattern Recognition · Computer Science 2021-10-04 Anjith George , Sebastien Marcel