Datasets:
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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=
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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=
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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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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=
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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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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
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