Silicone Mask Attack Dataset
The dataset contains videos of human faces with silicone masks designed for presentation attacks, providing high-quality data for face recognition, anti-spoofing, and attack detection research, supporting the development of robust recognition systems, detection algorithms, and deep learning models against mask-based biometric attacks in compliance with iBeta Level 2 certification standards
-
- Videos
- 6,500+
-
- Devices
- 5
- iBeta
- Liveness Detection
- Computer Vision
- Security
- Facial Recognition
- Anti-spoofing
The dataset contains videos of human faces with silicone masks designed for presentation attacks, providing high-quality data for face recognition, anti-spoofing, and attack detection research, supporting the development of robust recognition systems, detection algorithms, and deep learning models against mask-based biometric attacks in compliance with iBeta Level 2 certification standards
- iBeta
- Liveness Detection
- Computer Vision
- Security
- Facial Recognition
- Anti-spoofing
-
- Videos
- 6,500+
-
- Devices
- 5
Dataset Info
| Characteristic | Data |
| Description | Videos of people in silicone masks training algorithms to detect biometric hacking attempts. |
| Data types | Video |
| Tasks | Face recognition, Computer Vision |
| Total number of videos | 6,500 |
| Total number of people | 50 |
| Labeling | Only technical characteristics and metadata (age, gender, ethnicity) |
| Gender | Male, Female |
| Ethnicity | Caucasian (90%), African (10%) |
| Number of attributes | 31 |
attacks monthly
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Statistics
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- Number of devices of each type
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- Ethnicity in the dataset
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- Gender distribution
Technical
Characteristics
| Characteristic | Data |
| Video Extensions | mp4 |
| Video Resolutions | Min = 1920х1080, Max = 3840х2160 |
| Video Duration | 1-2 second |
| Number of background | 9 |
| Video Overlap | No more than 5% |
| Devices | Mi10s, Google Pixel 4, Samsung Galaxy A03s, iPhone 11, iPhone SE 2 and etc. |
Dataset Use Cases
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