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  The dataset consists of more than **32,300** spoofing attacks of **6** different types specifically curated for a passing **iBeta Level 2** and getting a certification. It is compliant with the **ISO 30107-3** standard, which sets the highest quality requirements for biometric testing and attack detection solutions.
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  By geting the **iBeta Level 2 certification**, biometric technology companies demonstrate their commitment to developing robust and reliable biometric systems that can effectively detect and prevent fraud -
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- **[Get the data](https://unidata.pro/datasets/ibeta-level-2-video-attacks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=ibeta-level-2)**
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  ## Attacks in the dataset
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  ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F352f8d1d97a5c1eb03967775f60fdcdb%2FFrame%20126%20(1).png?generation=1725872087101598&alt=media)
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  5. **Wrapped 3D Mask**: 3D cardboard mask attached to a mannequin
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  6. **Silicone Mask**: silicone masks on people
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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/ibeta-level-2-video-attacks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=ibeta-level-2) to discuss your requirements and pricing options.
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  ## Metadata for the dataset
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  Devices: **Mi10s, Google Pixel 4, Samsung Galaxy A03s, iPhone 11, iPhone SE 2**
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  The iBeta Level 2 dataset is an essential tool for the biometrics industry, as it helps to ensure that biometric systems meet the highest standards of anti-spoofing technology. This dataset is used by various biometric companies in various applications and products to test and improve their *biometric authentication solutions, face recognition systems and facial liveness detection methods.*
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- # 🌐 [UniData](https://unidata.pro/datasets/ibeta-level-2-video-attacks/?utm_source=huggingface&utm_medium=cpc&utm_campaign=ibeta-level-2) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects
 
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  The dataset consists of more than **32,300** spoofing attacks of **6** different types specifically curated for a passing **iBeta Level 2** and getting a certification. It is compliant with the **ISO 30107-3** standard, which sets the highest quality requirements for biometric testing and attack detection solutions.
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  By geting the **iBeta Level 2 certification**, biometric technology companies demonstrate their commitment to developing robust and reliable biometric systems that can effectively detect and prevent fraud -
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+ **[Get the data](https://unidata.pro/datasets/ibeta-level-2-video-attacks/?utm_source=huggingface&utm_medium=referral&utm_campaign=ibeta-level-2)**
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  ## Attacks in the dataset
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  ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F22059654%2F352f8d1d97a5c1eb03967775f60fdcdb%2FFrame%20126%20(1).png?generation=1725872087101598&alt=media)
 
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  5. **Wrapped 3D Mask**: 3D cardboard mask attached to a mannequin
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  6. **Silicone Mask**: silicone masks on people
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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/ibeta-level-2-video-attacks/?utm_source=huggingface&utm_medium=referral&utm_campaign=ibeta-level-2) to discuss your requirements and pricing options.
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  ## Metadata for the dataset
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  Devices: **Mi10s, Google Pixel 4, Samsung Galaxy A03s, iPhone 11, iPhone SE 2**
 
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  The iBeta Level 2 dataset is an essential tool for the biometrics industry, as it helps to ensure that biometric systems meet the highest standards of anti-spoofing technology. This dataset is used by various biometric companies in various applications and products to test and improve their *biometric authentication solutions, face recognition systems and facial liveness detection methods.*
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+ # 🌐 [UniData](https://unidata.pro/datasets/ibeta-level-2-video-attacks/?utm_source=huggingface&utm_medium=referral&utm_campaign=ibeta-level-2) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects