Datasets:
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README.md
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##Why Comprehensive Anti-Spoofing Data?
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Modern certification pipelines demand proof that a system resists all common attack vectors—not just prints or replays. This dataset delivers those vectors in one place, allowing you to:
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- Benchmark a model’s true generalisation
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- Fine-tune against rare but high-impact threats (e.g., silicone or textile masks)
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- Streamline audits by demonstrating coverage of every ISO 30107-3 attack category
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##Dataset Features
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- **Dataset Size:** ≈ 95 000 videos / image sequences spanning live captures and eleven spoof classes
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- **Attack Diversity:** 3D paper mask, wrapped 3D mask, photo print, mobile replay, display replay, cut-out 2D mask, silicone mask, latex mask, textile mask
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- **Active Liveness Cues:** Natural blinks, and head rotations included across live and mask sessions
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## Why Comprehensive Anti-Spoofing Data?
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Modern certification pipelines demand proof that a system resists all common attack vectors—not just prints or replays. This dataset delivers those vectors in one place, allowing you to:
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- Benchmark a model’s true generalisation
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- Fine-tune against rare but high-impact threats (e.g., silicone or textile masks)
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- Streamline audits by demonstrating coverage of every ISO 30107-3 attack category
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## Dataset Features
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- **Dataset Size:** ≈ 95 000 videos / image sequences spanning live captures and eleven spoof classes
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| 38 |
- **Attack Diversity:** 3D paper mask, wrapped 3D mask, photo print, mobile replay, display replay, cut-out 2D mask, silicone mask, latex mask, textile mask
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| 39 |
- **Active Liveness Cues:** Natural blinks, and head rotations included across live and mask sessions
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