2D Printed Mask and Replay Attack Videos Dataset
A multi-part video dataset for detecting 2D print attacks (printed photos) and replay attacks (faces displayed on screens).
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- Videos
- 26 436
- Computer Vision
- Machine learning
- Security
- Anti-spoofing
- Liveness Detection
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- Videos
- 26 436
Dataset Info
| Characteristic | Data |
| Description | Videos of individuals with printed masks and replay attacks |
| Data types | Video |
| Tasks | Anti-spoofing, Liveness Detection, Face Recognition |
| Number of videos | 26 436 |
| Name of categories | Video fakes, tolokers based spoofs (Videos of crowdworkers' faces displayed on computer or phone screens), video zoom, youdo heads (Videos of cut-out color printouts of faces, collected via YouDo), in-car videos and fakes |
| Labeling | Metadata (age, gender, ethnicity) |
| Gender | Male, Female |
attacks monthly
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Technical
Characteristics
| Characteristic | Data |
| Video extensions | Mp4, MOV |
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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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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Our team got in touch with UniData for purchasing video data. The team at UniData was transparent, timely, and pleasant to communicate and negotiate with. Their samples and descriptions aligned well with the data we received. We will certainly reach out to UniData again if we're in search of 3rd party video data.
Data is well organized and easy to…
Data is well organized and easy to consume. We could download and use it for training within few hours of receiving the data links.
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