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Liveness Detection: Replay attacks (5K+)
The dataset includes selfies from over 1,000 people. Later, a team of over 200 people made 5,000+ replay display attacks based on these selfies. The attacks provide diversity of lighting, devices, and screens
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Dataset Description:
- Over 1,000 individuals shared selfies
- Balanced mix of genders and ethnicities
- More than 5,000 display attacks crafted from these selfies
Real Life Selfies Description:
- Each person provided one selfie
- Selfies are at least 720p quality
- Faces are clear with no filters
Replay display attacks description:
- Videos last at least 12 seconds
- Cameras move slowly, showing attacks from various angles
Potential Use Cases:
Liveness detection: This dataset is ideal for training and evaluating liveness detection models, enabling researchers to distinguish between selfies and replay display attacks with high accuracy
Keywords: Display attacks, Antispoofing, Liveness Detection, Spoof Detection, Facial Recognition, Biometric Authentication, Security Systems, AI Dataset, Replay Attack Dataset, Anti-Spoofing Technology, Facial Biometrics, Machine Learning Dataset, Deep Learning
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