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# Liveness Detection - Video Classification
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The biometric attack dataset with **replay attacks** on the real videos of people. **Replay attack** involves presenting a pre-recorded video or previously captured footage as if it were occurring in real-time.
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The primary objective is to distinguish between genuine, real-time footage and manipulated recordings.
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Our dataset also explores the use of neural architectures, such as deep neural networks, to facilitate the identification of distinguishing patterns and textures in different regions of the face, increasing the accuracy and generalizability of the anti-spoofing models.
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### Metadata for the full dataset:
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- **replay.assignment_id** - unique identifier of the media file
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- **video_fps** - frames per second for video in the dataset
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# Content
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The dataset includes **files** folder with videos of people
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- **id**: id of the person,
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- **file**: link to access the display spoof attack video
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language:
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tags:
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- Liveness Detection
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- replay attacks
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- liveness detection systems
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- biometric data
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- anti-spoofing
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size_categories:
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- 10K<n<100K
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# Liveness Detection - Video Classification
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# The dataset is created on the basis of [2D Printed Mask and Replay Attack Videos Dataset](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=display-spoof-attack)
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The biometric attack dataset with **replay attacks** on the real videos of people. **Replay attack** involves presenting a pre-recorded video or previously captured footage as if it were occurring in real-time.
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The primary objective is to distinguish between genuine, real-time footage and manipulated recordings.
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Our dataset also explores the use of neural architectures, such as deep neural networks, to facilitate the identification of distinguishing patterns and textures in different regions of the face, increasing the accuracy and generalizability of the anti-spoofing models.
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## 💴 For Commercial Usage: Full version of the dataset includes 110,000+ photos of people, leave a request on **[our website](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=display-spoof-attack)** to buy the dataset
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### Metadata for the full dataset:
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- **replay.assignment_id** - unique identifier of the media file
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- **video_fps** - frames per second for video in the dataset
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## 💴 Buy the Dataset: This is just an example of the data. Leave a request on the [our website](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=display-spoof-attack) to discuss your requirements, learn about the price and buy the dataset
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# Content
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The dataset includes **files** folder with videos of people
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- **id**: id of the person,
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- **file**: link to access the display spoof attack video
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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 [our website](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=display-spoof-attack) to discuss your requirements, learn about the price and buy the dataset.
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## [Our Team](https://unidata.pro/datasets/2d-printed-mask-and-replay-attack-videos-dataset/?utm_source=huggingface-td&utm_medium=referral&utm_campaign=display-spoof-attack) provides high-quality data annotation tailored to your needs
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