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Modern face recognition systems remain vulnerable to spoofing attempts, including both physical presentation attacks and digital forgeries. Traditionally, these two attack vectors have been handled by separate models, each targeting its own…

Computer Vision and Pattern Recognition · Computer Science 2025-08-22 Andrei Balykin , Anvar Ganiev , Denis Kondranin , Kirill Polevoda , Nikolai Liudkevich , Artem Petrov

In this paper, we propose a novel and practical mechanism which enables the service provider to verify whether a suspect model is stolen from the victim model via model extraction attacks. Our key insight is that the profile of a DNN…

Cryptography and Security · Computer Science 2022-05-10 Zirui Peng , Shaofeng Li , Guoxing Chen , Cheng Zhang , Haojin Zhu , Minhui Xue

Face presentation attack detection (PAD) has been an urgent problem to be solved in the face recognition systems. Conventional approaches usually assume the testing and training are within the same domain; as a result, they may not…

Computer Vision and Pattern Recognition · Computer Science 2020-04-07 Guoqing Wang , Hu Han , Shiguang Shan , Xilin Chen

Facial recognition systems are vulnerable to physical (e.g., printed photos) and digital (e.g., DeepFake) face attacks. Existing methods struggle to simultaneously detect physical and digital attacks due to: 1) significant intra-class…

Computer Vision and Pattern Recognition · Computer Science 2025-04-02 Yongze Li , Ning Li , Ajian Liu , Hui Ma , Liying Yang , Xihong Chen , Zhiyao Liang , Yanyan Liang , Jun Wan , Zhen Lei

Lack of generalization to unseen domains/attacks is the Achilles heel of most face presentation attack detection (FacePAD) algorithms. Existing attempts to enhance the generalizability of FacePAD solutions assume that data from multiple…

Computer Vision and Pattern Recognition · Computer Science 2023-08-23 Naif Alkhunaizi , Koushik Srivatsan , Faris Almalik , Ibrahim Almakky , Karthik Nandakumar

Face recognition systems are widely deployed for biometric authentication. Despite this, it is well-known that, without any safeguards, face recognition systems are highly vulnerable to presentation attacks. In response to this security…

Computer Vision and Pattern Recognition · Computer Science 2023-08-29 M. Ibsen , C. Rathgeb , F. Brechtel , R. Klepp , K. Pöppelmann , A. George , S. Marcel , C. Busch

Biometric presentation attack detection is gaining increasing attention. Users of mobile devices find it more convenient to unlock their smart applications with finger, face or iris recognition instead of passwords. In this paper, we survey…

Computer Vision and Pattern Recognition · Computer Science 2020-05-04 Yomna Safaa El-Din , Mohamed N. Moustafa , Hani Mahdi

A face morphing attack image can be verified to multiple identities, making this attack a major vulnerability to processes based on identity verification, such as border checks. Various methods have been proposed to detect face morphing…

Computer Vision and Pattern Recognition · Computer Science 2021-09-28 Naser Damer , Noemie Spiller , Meiling Fang , Fadi Boutros , Florian Kirchbuchner , Arjan Kuijper

Unsupervised video person re-identification (reID) methods usually depend on global-level features. And many supervised reID methods employed local-level features and achieved significant performance improvements. However, applying…

Computer Vision and Pattern Recognition · Computer Science 2022-02-15 Xianghao Zang , Ge Li , Wei Gao , Xiujun Shu

3D mask face presentation attack detection (PAD) plays a vital role in securing face recognition systems from emergent 3D mask attacks. Recently, remote photoplethysmography (rPPG) has been developed as an intrinsic liveness clue for 3D…

Computer Vision and Pattern Recognition · Computer Science 2021-04-16 Zitong Yu , Xiaobai Li , Pichao Wang , Guoying Zhao

Recent advancements in Generative Adversarial Networks (GANs) have enabled photorealistic image generation with high quality. However, the malicious use of such generated media has raised concerns regarding visual misinformation. Although…

Computer Vision and Pattern Recognition · Computer Science 2024-04-02 Liviu-Daniel Ştefan , Dan-Cristian Stanciu , Mihai Dogariu , Mihai Gabriel Constantin , Andrei Cosmin Jitaru , Bogdan Ionescu

We present novel approaches involving generative adversarial networks and diffusion models in order to synthesize high quality, live and spoof fingerprint images while preserving features such as uniqueness and diversity. We generate live…

Computer Vision and Pattern Recognition · Computer Science 2024-03-22 W. Tang , D. Figueroa , D. Liu , K. Johnsson , A. Sopasakis

Latent fingerprints are one of the most widely used forensic evidence by law enforcement agencies. However, latent recognition performance is far from the exemplary performance of sensor fingerprint recognition due to deformations and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-26 Yusuf Artan , Bensu Alkan Semiz

Biometric time and attendance system is one of the most successful applications of biometric technology. One of the main advantage of a biometric time and attendance system is it avoids "buddy-punching". Buddy punching was a major loophole…

Computer Vision and Pattern Recognition · Computer Science 2012-08-09 Josphineleela Ramakrishnan , M. Ramakrishnan

Traditional security detection methods face three key challenges: inadequate data collection that misses critical security events, resource-intensive monitoring systems, and poor detection algorithms with high false positive rates. We…

Cryptography and Security · Computer Science 2025-06-06 Limin Wang , Lei Bu , Muzimiao Zhang , Shihong Cang , Kai Ye

Skin distortion is a long standing challenge in fingerprint matching, which causes false non-matches. Previous studies have shown that the recognition rate can be improved by estimating the distortion field from a distorted fingerprint and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-30 Xiongjun Guan , Yongjie Duan , Jianjiang Feng , Jie Zhou

Skin distortion is a long standing challenge in fingerprint matching, which causes false non-matches. Previous studies have shown that the recognition rate can be improved by estimating the distortion field from a distorted fingerprint and…

Computer Vision and Pattern Recognition · Computer Science 2024-04-29 Xiongjun Guan , Yongjie Duan , Jianjiang Feng , Jie Zhou

Presentation attack detection (PAD) subsystems are an important part of effective and user-friendly remote identity validation (RIV) systems. However, ensuring robust performance across diverse environmental and procedural conditions…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 John J. Howard , Richard O. Plesh , Yevgeniy B. Sirotin , Jerry L. Tipton , Arun R. Vemury

With the rapid progress of generative models, the current challenge in face forgery detection is how to effectively detect realistic manipulated faces from different unseen domains. Though previous studies show that pre-trained Vision…

Computer Vision and Pattern Recognition · Computer Science 2024-08-23 Anwei Luo , Rizhao Cai , Chenqi Kong , Yakun Ju , Xiangui Kang , Jiwu Huang , Alex C. Kot

Latent fingerprints are one of the most important and widely used evidence in law enforcement and forensic agencies worldwide. Yet, NIST evaluations show that the performance of state-of-the-art latent recognition systems is far from…

Computer Vision and Pattern Recognition · Computer Science 2017-04-07 Kai Cao , Anil K. Jain
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