Results 11 to 20 of about 4,067,204 (166)

Cross‐ethnicity face anti‐spoofing recognition challenge: A review

IET Biometrics, 2021
Face anti‐spoofing is critical to prevent face recognition systems from a security breach. The biometrics community has achieved impressive progress recently due to the excellent performance of deep neural networks and the availability of large datasets.
Ajian Liu, Xuan Li, Jun Wan, Yanyan Liang, Sergio Escalera, Hugo Jair Escalante, Meysam Madadi, Yi Jin, Zhuoyuan Wu, Xiaogang Yu, Zichang Tan, Qi Yuan, Ruikun Yang, Benjia Zhou, Guodong Guo, Stan Z. Li   +15 more
doaj   +2 more sources

Overview of satellite nav spoofing and anti-spoofing techniques [PDF]

Frontiers in Physics
In recent years, satellite navigation systems have witnessed widespread adoption across diverse fields, including military surveillance, precision agriculture, traffic monitoring, resource exploration, and disaster assessment. However, navigation signals
Cheng Lu, Zukun Lu, Zukun Lu, Zhe Liu, Zhe Liu, Long Huang, Long Huang, Feiqiang Chen, Feiqiang Chen   +8 more
doaj   +2 more sources

Overview of Anti-Spoofing Methods of Face Recognition Systems for Different Sensors and Complex Scenes [PDF]

Jisuanji gongcheng, 2021
As an important biometric recognition technology, face recognition has been widely used in daily life.Although significant progress has been made in this field, the existing face recognition systems are vulnerable to malicious attacks from illegal users ...
HUANG Yifang, WEI Dandan, WU Miao, LI Huibin, GUO Meng
doaj   +1 more source

Out of Domain Face Anti-spoofing: A Survey [PDF]

Jisuanji kexue yu tansuo, 2022
Face anti-spoofing (FAS), as an important means to protect face recognition models, can ensure that the system remains secure and reliable in the face of various presentation attacks.
SHI Yichen, FENG Jun, XIAO Lixuan, HE Jingjing, HU Jingjing
doaj   +1 more source

Face Anti-Spoofing Based on Deep Learning: A Comprehensive Survey

Applied Sciences
Face recognition has achieved tremendous success in both its theory and technology. However, with increasingly realistic attacks, such as print photos, replay videos, and 3D masks, as well as new attack methods like AI-generated faces or videos, face ...
Huifen Xing, Siok Yee Tan, Faizan Qamar, Yuqing Jiao   +3 more
doaj   +3 more sources

Self-Attention and MLP Auxiliary Convolution for Face Anti-Spoofing

IEEE Access, 2023
Face features, as the most widely adopted and essential biometric characteristic in identity verification and recognition, play a crucial role in ensuring security.
Hanqing Gu, Jiayin Chen, Fusu Xiao, Yi-Jia Zhang, Zhe-Ming Lu   +4 more
doaj   +1 more source

Progressive Transfer Learning for Face Anti-Spoofing. [PDF]

, 2022
Face anti-spoofing (FAS) techniques play an important role in defending face recognition systems against spoofing attacks. Existing FAS methods often require a large number of annotated spoofing face data to train effective anti-spoofing models ...
Quan, R, Yu, X, Wu, Y, Yang, Y
core   +1 more source

Face anti‐spoofing from the perspective of data sampling

Electronics Letters, 2023
Without deploying face anti‐spoofing countermeasures, face recognition systems can be spoofed by presenting a printed photo, a video, or a silicon mask of a genuine user.
Usman Muhammad, Mourad Oussalah
doaj   +1 more source

A Review on Face Anti-Spoofing [PDF]

, 2021
The biometric system is a security technology that uses information based on a living person's characteristics to verify or recognize the identity, such as facial recognition.
Perdana, Rizky Naufal, Ardiyanto, Igi, Nugroho, Hanung Adi   +2 more
core   +1 more source

Face Anti-Spoofing : Detection, Generalization, and Visualization [PDF]

, 2021
Face anti-spoofing is the process of distinguishing genuine faces and face presentation attacks: attackers presenting spoofing faces (e.g. photograph, digital screen, and mask) to the face recognition system and attempting to be authenticated as the ...
Liu, Yaojie
core   +1 more source