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- # Attacks with 2D Printed Masks of Indian People
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  The dataset consists of videos of individuals wearing printed 2D masks of different kinds and directly looking at the camera. Videos are filmed in different lightning conditions and in different places (*indoors, outdoors*). Each video in the dataset has an approximate duration of 3-4 seconds.
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  ### Types of videos in the dataset:
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  Inside the **"attacks"** folder there are 10 sub-folders and corresponding files inside:
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  - **1**- Real videos without glasses
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  - **9** - Mask with printed glasses held by hands
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  - **10** - Mask with printed and real glasses held by hands
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  ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fe0809e4372f31481ccbdb8869bf03b09%2Fattack1.png?generation=1691564747323159&alt=media)
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  ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fcb1da224833b3e3aee7cdb4cd55922b7%2Fattack2.png?generation=1691564762819477&alt=media)
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  The dataset serves as a valuable resource for computer vision, anti-spoofing tasks, video analysis, and security systems. It allows for the development of algorithms and models that can effectively detect attacks perpetrated by individuals wearing printed 2D masks.
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- Studying the dataset may lead to the development of improved security systems, surveillance technologies, and solutions to mitigate the risks associated with masked individuals carrying out attacks.
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- # Get the dataset
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- ### This is just an example of the data
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- Leave a request on [**https://trainingdata.pro/data-market**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=attacks-with-2d-printed-masks-of-indian-people) to discuss your requirements, learn about the price and buy the dataset.
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  # Content
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  ### The folder **"attacks"** includes 10 folders:
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  - **type_2**: link to the real video with glasses,
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  - **type_3,... type_10**: links to the videos with different types of attacks, identified earlier
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- # Attacks might be collected in accordance with your requirements.
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- ## [**TrainingData**](https://trainingdata.pro/data-market?utm_source=huggingface&utm_medium=cpc&utm_campaign=attacks-with-2d-printed-masks-of-indian-people) provides high-quality data annotation tailored to your needs
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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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+ # Attacks with 2D Printed Masks of Indian People - Biometric Attack Dataset
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  The dataset consists of videos of individuals wearing printed 2D masks of different kinds and directly looking at the camera. Videos are filmed in different lightning conditions and in different places (*indoors, outdoors*). Each video in the dataset has an approximate duration of 3-4 seconds.
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+ # 💴 For Commercial Usage: Full version of the dataset includes 3394 videos, leave a request on **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=attacks-with-2d-printed-masks-of-indian-people)** to buy the dataset
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  ### Types of videos in the dataset:
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  Inside the **"attacks"** folder there are 10 sub-folders and corresponding files inside:
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  - **1**- Real videos without glasses
 
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  - **9** - Mask with printed glasses held by hands
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  - **10** - Mask with printed and real glasses held by hands
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  ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fe0809e4372f31481ccbdb8869bf03b09%2Fattack1.png?generation=1691564747323159&alt=media)
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  ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fcb1da224833b3e3aee7cdb4cd55922b7%2Fattack2.png?generation=1691564762819477&alt=media)
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  The dataset serves as a valuable resource for computer vision, anti-spoofing tasks, video analysis, and security systems. It allows for the development of algorithms and models that can effectively detect attacks perpetrated by individuals wearing printed 2D masks.
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+ The dataset comprises videos of genuine facial presentations using various methods, including 2D masks and printed photos, as well as real and spoof faces. It proposes a novel approach that learns and extracts facial features to prevent spoofing attacks, based on deep neural networks and advanced biometric techniques.
 
 
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+ Our results show that this technology works effectively in securing most applications and prevents unauthorized access by distinguishing between genuine and spoofed inputs. Additionally, it addresses the challenging task of identifying unseen spoofing cues, making it one of the most effective techniques in the field of anti-spoofing research.
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+ # 💴 Buy the Dataset: This is just an example of the data. Leave a request on **[https://trainingdata.pro/datasets](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=attacks-with-2d-printed-masks-of-indian-people) to discuss your requirements, learn about the price and buy the dataset**
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  # Content
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  ### The folder **"attacks"** includes 10 folders:
 
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  - **type_2**: link to the real video with glasses,
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  - **type_3,... type_10**: links to the videos with different types of attacks, identified earlier
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+ ## **[TrainingData](https://trainingdata.pro/datasets?utm_source=huggingface&utm_medium=cpc&utm_campaign=attacks-with-2d-printed-masks-of-indian-people)** provides high-quality data annotation tailored to your needs
 
 
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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, phone attack dataset, face anti spoofing, large-scale face anti spoofing, rich annotations anti spoofing dataset, cut prints spoof attack*