---
license: cc-by-nc-nd-4.0
task_categories:
- video-classification
tags:
- people
- mask
- computer vison
- facial recognition
- verification
- cyber security
size_categories:
- 10K<n<100K
---
# 2D Masks with Eyeholes Attacks
The dataset comprises **11,200+** videos of people wearing of holding 2D printed masks with eyeholes captured using **5** different devices. This extensive collection is designed for research in presentation attacks, focusing on various **detection methods**, primarily aimed at meeting the requirements for **iBeta Level 1 & 2 certification.** Specifically engineered to challenge **facial recognition** and enhance **spoofing detection** techniques.

By utilizing this dataset, researchers and developers can advance their understanding and capabilities in **biometric security** and **liveness detection technologies**. - **[Get the data](https://unidata.pro/datasets/2d-masks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=2d-masks-pad-attacks)**
## Attacks in the dataset
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F589023f5a5202dd588e5d9df56747037%2FFrame%20166.png?generation=1731498279480466&alt=media)
The attacks were recorded in various settings, showcasing individuals with different attributes. Each photograph features human faces adorned with 2D masks, simulating potential spoofing attempts in facial recognition systems.

**Variants of backgrounds and attributes in the dataset**:
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2Fbf3ed70a8a519ebb4bbdd8fc634bd4f3%2FFrame%20146%20(2).png?generation=1730208154622175&alt=media)
# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/2d-masks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=2d-masks-pad-attacks) to discuss your requirements and pricing options.
Researchers can utilize this dataset to explore detection technology and recognition algorithms that aim to prevent impostor attacks and improve authentication processes.
## Metadata for the dataset
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F599c49641aa40b28eef7684a086fb98b%2FFrame%20161%20(4).png?generation=1731498379460267&alt=media)
**Variables in .csv files:**

-   **name:** filename of the printed 2D mask
-   **path:** link-path for the original video
-   **type:** type(wearing or holding) of printed mask

The dataset provides a robust foundation for achieving higher detection accuracy and advancing liveness detection methods, which are essential for preventing identity fraud and ensuring reliable biometric verification.

# 🌐 [UniData](https://unidata.pro/datasets/2d-masks/utm_source=huggingface&utm_medium=cpc&utm_campaign=2d-masks-pad-attacks) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects