README.md · AxonData/Display_replay

metadata

license: cc-by-4.0
task_categories:
  - image-classification
  - image-feature-extraction
  - image-segmentation
language:
  - en
size_categories:
  - 1K<n<10K

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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Left: Real selfie; Right: Display attack Left: Real selfie; Right: Display attack

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