README.md

metadata

license: cc-by-4.0
task_categories:
  - image-feature-extraction
  - image-classification
  - video-classification
language:
  - en
tags:
  - display-replay-attack
  - replay-attack
  - face-anti-spoofing
  - liveness-detection
  - presentation-attack-detection
  - pad
  - biometrics
  - face-recognition
  - spoofing
  - monitor-replay
  - laptop-replay
  - smartphone-replay
  - iso-30107-3
  - ibeta-level-1
  - idiap-replay-attack-baseline
size_categories:
  - 1K<n<10K

Face Anti Spoofing Replay Dataset

iBeta Level 1 Dataset

Liveness Detection: Replay attacks. 5,000+ videos of display replay monitor attacks 12+ sec and real photos. The attacks provide diversity of lighting, devices, and screens

Full version of dataset is availible for commercial usage - leave a request on our website Axon Labs to purchase the dataset 💰

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