journal article·2025Open access

PNSS: Unknown Face Presentation Attack Detection with Pseudo Negative Sample Synthesis

Hongyang Wang, Yichen Shi, Jun Feng, Zitong Yu, Zhuofu Tao

Computers, Materials & Continua· Volume 83· Issue 2

Abstract

Face Presentation Attack Detection (fPAD) plays a vital role in securing face recognition systems against various presentation attacks. While supervised learning-based methods demonstrate effectiveness, they are prone to over... | Find, read and cite all the research you need on Tech Science Press
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Face recognition and analysis · Biometric Identification and Security · Face and Expression Recognition

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

References (40)

Show source-provided references
1. Learning meta face recognition in unseen domains
2. Yu Z, Qin Y, Li X, Zhao C, Lei Z, Zhao G. Deep learning for face anti-spoofing: a survey. arXiv:2106.14948. 2021.10.1109/TPAMI.2022.3215850 ↗
3. CASIA-SURF CeFA: a benchmark for multi-modal cross-ethnicity face anti-spoofing
4. Celeba-spoof: large-scale face anti-spoofing dataset with rich annotations
5. Unified unsupervised and semi-supervised domain adaptation network for cross-scenario face anti-spoofing10.1016/j.patcog.2021.107888 ↗
6. Adversarial learning and decomposition-based domain generalization for face anti-spoofing10.1016/j.patrec.2021.10.014 ↗
7. Csurka G. Domain adaptation for visual applications: a comprehensive survey. arXiv:1702.05374. 2017.10.1007/978-3-319-58347-1 ↗
8. Zhou K, Liu Z, Qiao Y, Xiang T, Loy CC. Domain generalization: a survey. arXiv:2103.02503. 2022.10.1109/TPAMI.2022.3195549 ↗
9. Anomaly detection-based unknown face presentation attack detection
10. One-class convolutional neural network10.1109/LSP.2018.2889273 ↗
11. de Freitas Pereira · Computer Vision—ACCV 2012 Workshops · 2012 · 7728
12. Secure face unlock: spoof detection on smartphones10.1109/TIFS.2016.2578288 ↗
13. Face antispoofing using speeded-up robust features and fisher vector encoding
14. Face liveness detection with component dependent descriptor
15. Searching central difference convolutional networks for face anti-spoofing
16. NAS-FAS: static-dynamic central difference network search for face anti-spoofing10.1109/TPAMI.2020.3036338 ↗
17. Ming Z, Yu Z, Al-Ghadi M, Visani M, MuzzamilLuqman M, Burie JC. Vitranspad: video transformer using convolution and self-attention for face presentation attack detection. arXiv:2203.01562. 2022.10.1109/ICIP46576.2022.9897560 ↗
18. Learning deep models for face antispoofing: binary or auxiliary supervision
19. Face anti-spoofing by fusing high and low frequency features for advanced generalization capability
20. Face antispoofing with human material perception
21. Remote heart rate measurement from highly compressed facial videos: an end-to-end deep learning solution with video enhancement
22. One-class face anti-spoofing via spoof cue map-guided feature learning
23. Narayan K, Patel VM. Hyp-OC: hyperbolic one class classification for face anti-spoofing. arXiv:2404.14406. 2024.10.1109/FG59268.2024.10581913 ↗
24. Multi-scale patch-based representation learning for image anomaly detection and segmentation
25. Active authentication using an autoencoder regularized cnn-based one-class classifier
26. Dual-minimax probability machines for one-class mobile active authentication
27. An anomaly detection approach to face spoofing detection: a new formulation and evaluation protocol
28. Vos: learning what you don’t know by virtual outlier synthesis
29. Focal loss for dense object detection
30. Pairwise confusion for fine-grained visual classification
31. OULU-NPU: a mobile face presentation attack database with real-world variations
32. Face spoof detection with image distortion analysis10.1109/TIFS.2015.2400395 ↗
33. On the effectiveness of local binary patterns in face antispoofing
34. Joint face detection and alignment using multitask cascaded convolutional networks10.1109/LSP.2016.2603342 ↗
35. Deep face recognition
36. Paszke A, Gross S, Chintala S, Chanan G, Yang E, DeVito Z, et al. Automatic differentiation in pytorch. 2017 [cited 2024 Dec 30]. Available from: https://openreview.net/forum?id=BJJsrmfCZ.
37. Schölkopf · Advances in Neural Information Processing Systems (NIPS) · 1999
38. Support vector data description10.1023/B:MACH.0000008084.60811.49 ↗
39. Scikit-learn: machine learning in Python
40. Combining multiple one-class classifiers for anomaly based face spoofing attack detection