# Face Anti-Spoofing Based on Deep Learning: A Comprehensive Survey
## Abbreviations
(2018)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Face flashing: A secure liveness detection protocol based on light reflections. _arXiv_**2018**, arXiv:1801.01949. [CrossRef]
* _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON] Efficient face spoofing detection with flash. _IEEE Trans. Biom. Behav. Identity Sci._**2021**, \(3\), 535-549. [CrossRef]
* _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] FaceRevelio: A face liveness detection system for smartphones with a single front camera. In Proceedings of the 26 th Annual International Conference on Mobile Computing and Networking, London, UK, 21-25 September 2020; pp. 1-13. * _[PERSON] et al. (2021)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Aurora guard: Reliable face anti-spoofing via mobile lighting system. _arXiv_**2021**, arXiv:2102.00713. [CrossRef]
* _[PERSON] et al. (2023)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] CloudNet: A LiDAR-based face anti-spoofing model that is robust against light variation. _IEEE Access_**2023**, _11_, 16984-16993. [CrossRef]
* _[PERSON] et al. (2022)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Mask does not matter: Anti-spoofing face authentication using mmWave without on-site registration. In Proceedings of the 28 th Annual International Conference on Mobile Computing and Networking, Sydney, NSW, Australia, 17-21 October 2022; pp. 310-323. * _[PERSON] et al. (2023)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Anti-spoofing facial authentication based on cots rfid. _IEEE Trans. Mob. Comput._**2023**, _23_, 4228-4245. [CrossRef]
* _[PERSON] et al. (2022)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Where are the dots: Hardening face authentication on smartphones with unforgeable eye movement patterns. _IEEE Trans. Inf. Forensics Secur._**2022**, _18_, 1295-1308. [CrossRef]
* _[PERSON] et al. (2020)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Auto-fas: Searching lightweight networks for face anti-spoofing. In Proceedings of the ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Virtual, 4-9 May 2020; pp. 996-1000. * _[PERSON] et al. (2024)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] M3 FAS: An Accurate and Robust MultiModal Mobile Face Anti-Spoofing System. _IEEE Trans. Dependable Secur. Comput._**2024**, _21_, 5650-5666. [CrossRef]
* _[PERSON] et al. (2012)_ [PERSON]; [PERSON]; [PERSON] On the effectiveness of local binary patterns in face anti-spoofing. In Proceedings of the 2012 BIOSIG-Proceedings of the International Conference of Biometrics Special Interest Group (BIOSIG), Darmstadt, Germany, 6-7 September 2012; pp. 1-7. * _[PERSON] (2013)_ [PERSON]; [PERSON] [PERSON]L. Shape and texture based countermeasure to protect face recognition systems against mask attacks. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, Portland, OR, USA, 23-28 June 2013; pp. 111-116. * _[PERSON] et al. (2015)_ [PERSON]; [PERSON]; [PERSON]; [PERSON] Using visual rhythms for detecting video-based facial spoof attacks. _IEEE Trans. Inf. Forensics Secur._**2015**, _10_, 1025-1038. [CrossRef]
* _[PERSON] et al. (2016)_ [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] The replay-mobile face presentation-attack database. In Proceedings of the 2016 international conference of the Biometrics Special Interest Group (BIOSIG), Darmstadt, Germany, 21-23 September 2016; pp. 1-7. * _[PERSON] et al. (2017)_ [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] OULU-NPU: A mobile face presentation attack database with real-world variations. In Proceedings of the 2017 12 th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), Washington, DC, USA, 30 May-3 June 2017; pp. 612-618. * _[PERSON] et al. (2018)_ [PERSON]; [PERSON]; [PERSON] Learning deep models for face anti-spoofing: Binary or auxiliary supervision.