Research map / Label-efficient and robust learning / Domain adaptation and generalization
Cross-Domain Face Presentation Attack Detection via Multi-Domain Disentangled Representation Learning
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use multi-domain disentangled representation learning | Cross-domain face PAD · Protocol 1: [O, C, I]→M, [O, M, I]→C, [O, C, M]→I, [I, C, M]→O | HTER (%): 30.25 -> 17.02; 33.97 -> 19.68; 35.21 -> 20.87; 28.74 -> 25.02 | Helped |
| Add DR-Net for disentangled representation learning (ablation) | Cross-domain face PAD · Protocol 1: four cross-domain tests | HTER (%): 26.43 -> 17.02; 31.43 -> 19.68; 29.56 -> 20.87; 27.23 -> 25.02 | Helped |
| Add MD-Net for multi-domain feature learning (ablation) | Cross-domain face PAD · Protocol 1: four cross-domain tests | HTER (%): 18.07 -> 17.02; 24.85 -> 19.68; 22.44 -> 20.87; 26.78 -> 25.02 | Helped |
| Add the cross-entropy loss LCE to MD-Net (ablation) | Cross-domain face PAD · Protocol 1: four cross-domain tests | HTER (%): 18.07 -> 17.02; 24.27 -> 19.68; 22.21 -> 20.87; 26.77 -> 25.02 | Helped |
| Add the reconstruction loss LREC to MD-Net (ablation) | Cross-domain face PAD · Protocol 1: four cross-domain tests | HTER (%): 18.14 -> 17.02; 21.03 -> 19.68; 21.47 -> 20.87; 26.21 -> 25.02 | Helped |
Closest papers by meaning
- Multi-Domain Incremental Learning for Face Presentation Attack Detection (AAAI 2024 · similarity 0.88)
- Triple Feature Disentanglement for One-Stage Adaptive Object Detection (AAAI 2024 · similarity 0.85)
- Masked Face Recognition with Generative-to-Discriminative Representations (ICML 2024 · similarity 0.84)
- Test-Time Domain Generalization for Face Anti-Spoofing (CVPR 2024 · similarity 0.83)
- Critical Forgetting-Based Multi-Scale Disentanglement for Deepfake Detection (AAAI 2025 · similarity 0.83)
- FSFM: A Generalizable Face Security Foundation Model via Self-Supervised Facial Representation Learning (CVPR 2025 · similarity 0.83)
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