README.md

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

## Face Anti Spoofing Replay 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](https://axonlabs.pro/) to purchase the dataset 💰

![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F20109613%2F78db306cc3efb77b321a05c82261a40f%2FFrame%2066-2.png?generation=1743407742369077&alt=media)
Left: Real selfie; Right: Display attack
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F20109613%2F140cd478a2838192b815a07112e2ff25%2FFrame%2064-2.png?generation=1743407755587365&alt=media)
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