Face Presentation Attack Detection
17 papers with code • 2 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Face Presentation Attack Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
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WMCA
CASIA-SURF
Replay-Mobile
OULU-NPU
Most implemented papers
VLAD-VSA: Cross-Domain Face Presentation Attack Detection with Vocabulary Separation and Adaptation
In this paper, the VLAD aggregation method is adopted to quantize local features with visual vocabulary locally partitioning the feature space, and hence preserve the local discriminability.
One-Class Knowledge Distillation for Face Presentation Attack Detection
Under this framework, a teacher network is trained with source domain samples to provide discriminative feature representations for face PAD.
Fairness in Face Presentation Attack Detection
Face recognition (FR) algorithms have been proven to exhibit discriminatory behaviors against certain demographic and non-demographic groups, raising ethical and legal concerns regarding their deployment in real-world scenarios.
SynthASpoof: Developing Face Presentation Attack Detection Based on Privacy-friendly Synthetic Data
To target these legal and technical challenges, this work presents the first synthetic-based face PAD dataset, named SynthASpoof, as a large-scale PAD development dataset.
FedSIS: Federated Split Learning with Intermediate Representation Sampling for Privacy-preserving Generalized Face Presentation Attack Detection
naiftt/fedsis
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In FedSIS, a hybrid Vision Transformer (ViT) architecture is learned using a combination of FL and split learning to achieve robustness against statistical heterogeneity in the client data distributions without any sharing of raw data (thereby preserving privacy).
Face Presentation Attack Detection by Excavating Causal Clues and Adapting Embedding Statistics
meilfang/cf-pad
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We excavate the causal factors hidden in the high-level representation via counterfactual intervention.
SynFacePAD 2023: Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data
zi-yuanyang/ijcb-synfacepad-dig
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This paper presents a summary of the Competition on Face Presentation Attack Detection Based on Privacy-aware Synthetic Training Data (SynFacePAD 2023) held at the 2023 International Joint Conference on Biometrics (IJCB 2023).
