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--- |
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license: cc-by-nc-nd-4.0 |
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task_categories: |
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- video-classification |
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tags: |
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- people |
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- mask |
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- computer vison |
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- facial recognition |
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- verification |
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- cyber security |
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size_categories: |
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- 10K<n<100K |
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--- |
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# 2D Masks with Eyeholes Attacks |
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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. |
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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=referral&utm_campaign=2d-masks-pad-attacks)** |
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## Attacks in the dataset |
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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. |
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**Variants of backgrounds and attributes in the dataset**: |
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.png?generation=1730208154622175&alt=media) |
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# 💵 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=referral&utm_campaign=2d-masks-pad-attacks) to discuss your requirements and pricing options. |
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Researchers can utilize this dataset to explore detection technology and recognition algorithms that aim to prevent impostor attacks and improve authentication processes. |
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## Metadata for the dataset |
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.png?generation=1731498379460267&alt=media) |
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**Variables in .csv files:** |
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- **name:** filename of the printed 2D mask |
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- **path:** link-path for the original video |
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- **type:** type(wearing or holding) of printed mask |
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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. |
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# 🌐 [UniData](https://unidata.pro/datasets/2d-masks/utm_source=huggingface&utm_medium=referral&utm_campaign=2d-masks-pad-attacks) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects |
