2D Print Attacks and Silicone Masks Attacks Dataset
Photos and videos of people using 2D-printed faces or silicone masks (with accessories), plus shots without masks
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-
- images
- 16,867
-
- videos
- 2,929
- iBeta
- Computer Vision
- Machine learning
- Security
- Anti-spoofing
- Liveness Detection
-
- images
- 16,867
-
- videos
- 2,929
Dataset Info
| Characteristic | Data |
| Description | Videos of individuals wearing or holding printed/silicone masks |
| Data types | Video, Image |
| Tasks | Liveness Detection, Computer Vision, iBeta |
| Number of image | 16,867 images (12,656 2D-print, 4,211 silicone) |
| Number of video | 2,929 videos (2,480 2D-print, 449 silicone) |
| Labeling | Metadata (age, gender, ethnicity) |
| Gender | Male, Female |
| Name of attributes | Wigs, glasses, beards/mustaches, masks, clothing, etc |
Technical
Characteristics
| Characteristic | Data |
| Video extension | mp4 |
| Image extension | JPG |
Industries
Finance:
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Banking:
Using biometric authentication for secure access to bank accounts and transactions.
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E-commerce:
Using facial recognition technologies to prevent fraud in online purchases and authenticate users.
Security:
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Access Control Integration:
Implementation of solutions based on iBeta Level 2 to enhance security levels across various sectors, including physical security and access to digital resources.
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Biometric Verification:
A method of confirming identity using unique biological traits, such as facial features, to authenticate individuals
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Cybersecurity:
Applying biometric attack detection techniques for fraud defense
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