| | --- |
| | license: cc-by-4.0 |
| | task_categories: |
| | - image-feature-extraction |
| | - image-classification |
| | - video-classification |
| | language: |
| | - en |
| | tags: |
| | - liveness detection |
| | - anti-spoofing |
| | - biometrics |
| | - facial recognition |
| | - machine learning |
| | - deep learning |
| | - AI |
| | - paper mask attack |
| | - iBeta certification |
| | - PAD attack |
| | - security |
| | - ibeta |
| | - face recognition |
| | - pad |
| | - authentication |
| | - fraud |
| | 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 |
| |
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| | ## Full version of dataset is availible for commercial usage - leave a request on our website [Axon Labs](https://axonlab.ai/?utm_source=hugging-face&utm_medium=cpc&utm_campaign=profile&utm_content=profile_link) to purchase the dataset 💰 |
| |
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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 |
| |
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| | ## Real Life Selfies Description: |
| |
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| | - Each person provided one selfie |
| | - Selfies are at least 720p quality |
| | - Faces are clear with no filters |
| |
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| | ## Replay display attacks description: |
| |
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| | - Videos last at least 12 seconds |
| | - Cameras move slowly, showing attacks from various angles |
| |
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| | ## 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 |
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| | - 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 |
