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README.md
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- image-classification
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language:
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- en
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---
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# Mobile Face Liveness Detection
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The dataset consists of videos featuring individuals wearing various types of masks. Videos are recorded under **different lighting conditions** and with **different attributes** (*glasses, masks, hats, hoods, wigs, and mustaches for men*).
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In the dataset, there are **4 types of videos** filmed on mobile devices:
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- **2D mask with holes for eyes** - demonstration of an attack with a paper/cardboard mask (*mask*)
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# Get the Dataset
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## This is just an example of the data
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# Content
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The folder **files** includes:
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- **file**: link to access the file,
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- **type**: type of the video (*real, mask, outline, mask_cut*)
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More datasets in TrainingData's Kaggle account: **<https://www.kaggle.com/trainingdatapro/datasets>**
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TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets**
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*keywords: ibeta level 1, ibeta level 2, liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, face spoofing database, face anti-spoofing, face recognition, face detection, face identification, human video dataset, video dataset, presentation attack detection, presentation attack dataset, 2d print attacks, print 2d attacks dataset, printed 2d masks dataset, spoofing in 2D face recognition, facial masks, 2D face recognition systems, detecting face spoofing attacks, detecting presentation attacks, computer vision, surveillance face anti-spoofing, face liveness detection software solution*
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- image-classification
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language:
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- en
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tags:
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- ibeta
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- replay attack
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- video
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- liveness detection
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- biometric
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- anti-spoofing
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size_categories:
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- 10K<n<100K
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---
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# Mobile Face Liveness Detection
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The dataset consists of videos featuring individuals wearing various types of masks. Videos are recorded under **different lighting conditions** and with **different attributes** (*glasses, masks, hats, hoods, wigs, and mustaches for men*).
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# The dataset is created on the basis of [iBeta Level 1 Dataset](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=biometric-attacks-in-different-lighting)
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In the dataset, there are **4 types of videos** filmed on mobile devices:
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- **2D mask with holes for eyes** - demonstration of an attack with a paper/cardboard mask (*mask*)
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# Get the Dataset
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## This is just an example of the data
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## 👉 Legally sourced datasets and carefully structured for AI training and model development. Explore samples from our dataset of 25,000+ human images & videos - [Full dataset](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=on-device-face-liveness-detection)
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# Content
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The folder **files** includes:
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- **file**: link to access the file,
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- **type**: type of the video (*real, mask, outline, mask_cut*)
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#**🚀 You can learn more about our high-quality unique datasets [here](https://unidata.pro/datasets/ibeta-level-1-video-attacks/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=on-device-face-liveness-detection)**
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*keywords: ibeta level 1, ibeta level 2, liveness detection systems, liveness detection dataset, biometric dataset, biometric data dataset, biometric system attacks, anti-spoofing dataset, face liveness detection, deep learning dataset, face spoofing database, face anti-spoofing, face recognition, face detection, face identification, human video dataset, video dataset, presentation attack detection, presentation attack dataset, 2d print attacks, print 2d attacks dataset, printed 2d masks dataset, spoofing in 2D face recognition, facial masks, 2D face recognition systems, detecting face spoofing attacks, detecting presentation attacks, computer vision, surveillance face anti-spoofing, face liveness detection software solution*
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