Real masks and spoof faces: On the masked face presentation attack detection

Author:

Fang Meiling,Damer Naser,Kirchbuchner Florian,Kuijper Arjan

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference42 articles.

1. Ongoing Face Recognition Vendor Test (FRVT) Part 6B: Face recognition accuracy with face masks using post-COVID-19 algorithms;Ngan,2020

2. The effect of wearing a mask on face recognition performance: an exploratory study;Damer,2020

3. Extended evaluation of the effect of real and simulated masks on face recognition performance;Damer;IET Biom.,2021

4. A survey on 3d mask presentation attack detection and countermeasures;Jia;Pattern Recognit.,2020

5. Face spoofing detection under super-realistic 3d wax face attacks;Jia;Pattern Recognit. Lett.,2021

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1. Detection of COVID-19 Pandemic Face Mask Using ConvNet in Busy Environments;Intelligent Technologies for Research and Engineering;2024-07-09

2. Detection of Adversarial Facial Accessory Presentation Attacks Using Local Face Differential;ACM Transactions on Multimedia Computing, Communications, and Applications;2024-03-27

3. Deep learning techniques for biometric security: A systematic review of presentation attack detection systems;Engineering Applications of Artificial Intelligence;2024-03

4. Fairness in face presentation attack detection;Pattern Recognition;2024-03

5. Face Presentation Attack Detection by Excavating Causal Clues and Adapting Embedding Statistics;2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV);2024-01-03

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