Generative Domain Adaptation for Face Anti-Spoofing-Reference-Cited by-同舟云学术

Generative Domain Adaptation for Face Anti-Spoofing

Published:2022 Issue: Volume: Page:335-356
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Zhou Qianyu^ORCID,Zhang Ke-Yue^ORCID,Yao Taiping^ORCID,Yi Ran^ORCID,Sheng Kekai^ORCID,Ding Shouhong^ORCID,Ma Lizhuang^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-20065-6_20

Reference116 articles.

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2. Boulkenafet, Z., Komulainen, J., Hadid, A.: Face anti-spoofing based on color texture analysis. In: IEEE International Conference on Image Processing (ICIP), pp. 2636–2640. IEEE (2015)

3. Boulkenafet, Z., Komulainen, J., Hadid, A.: Face spoofing detection using colour texture analysis. IEEE Trans. Inf. Forensics Secur. (TIFS) 11(8), 1818–1830 (2016)

4. Boulkenafet, Z., Komulainen, J., Li, L., Feng, X., Hadid, A.: Oulu-NPU: a mobile face presentation attack database with real-world variations. In: 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), pp. 612–618. IEEE (2017)

5. Chang, W.L., Wang, H.P., Peng, W.H., Chiu, W.C.: All about structure: adapting structural information across domains for boosting semantic segmentation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1900–1909 (2019)

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3. A Comprehensive Survey on Test-Time Adaptation Under Distribution Shifts;International Journal of Computer Vision;2024-07-18

4. Domain Generalization via Ensemble Stacking for Face Presentation Attack Detection;International Journal of Computer Vision;2024-06-25

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