2D Printed Photos Attacks and Replay Attacks Images Dataset
A multi-part image dataset for detecting 2D print attacks (printed photos) and replay attacks (faces displayed on screens).
-
- images
- 4,1M+
-
- people
- 80,000+
- Computer Vision
- Machine learning
- Security
- Anti-spoofing
- Liveness Detection
A multi-part image dataset for detecting 2D print attacks (printed photos) and replay attacks (faces displayed on screens).
- Computer Vision
- Machine learning
- Security
- Anti-spoofing
- Liveness Detection
-
- images
- 4,1M+
-
- people
- 80,000+
Dataset Info
| Characteristic | Data |
| Description | Images of individuals with printed masks and replay attack |
| Data types | Image |
| Tasks | Anti-spoofing, Liveness Detection, Face Recognition |
| Number of image | 4,1M+ |
| Number of people | 80,000+ |
| Name of categories | archive(Faces displayed on screens), color(Color printouts of faces), easy(Masked faces on screens), frame, mask, print, faces on screen, all(Color printouts (generic)), bald, tablet, fake, Moscow newspapers, paper, mask annotated, paper photo |
| Labeling | Metadata (age, gender, ethnicity) |
| Gender | Male, Female |
attacks monthly
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Technical
Characteristics
| Characteristic | Data |
| Image extension | JPG |
| Extension of labeling file | Bbox, json |
Industries
Finance:
-
Banking:
Using biometric authentication for secure access to bank accounts and transactions.
-
E-commerce:
Using facial recognition technologies to prevent fraud in online purchases and authenticate users.
Security:
-
Biometric Verification:
A method of confirming identity using unique biological traits, such as facial features, to authenticate individuals
-
Cybersecurity:
Applying biometric attack detection techniques for fraud defense
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