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Printed 2D Masks Attacks Dataset

It is a high-quality masks biometric attacks dataset featuring over 4,800 videos of people wearing or holding 2D printed masks. Designed for training facial recognition, liveness detection, and fraud prevention systems, the dataset also supports research for iBeta Level 1 & 2 certification compliance.

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  • videos
    4,800+
  • devices
    5
  • iBeta
  • Liveness Detection
  • Computer Vision
  • Security
  • Anti-spoofing
  • Machine learning

It is a high-quality masks biometric attacks dataset featuring over 4,800 videos of people wearing or holding 2D printed masks. Designed for training facial recognition, liveness detection, and fraud prevention systems, the dataset also supports research for iBeta Level 1 & 2 certification compliance.

Get in touch Download sample
  • iBeta
  • Liveness Detection
  • Computer Vision
  • Security
  • Anti-spoofing
  • Machine learning
  • videos
    4,800+
  • devices
    5

Dataset Info

Characteristic Data
Description Videos of individuals wearing or holding 2D masks
Data types Video
Tasks Liveness Detection, Computer Vision, iBeta
Number of video 4 800+
Labeling Metadata (age, gender, ethnicity, devices)
Gender Male, Female
Number of attributes 31
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Statistics

Devices in the dataset
Gender distribution

Technical
Characteristics

Characteristic Data
Video extension mp4, MOV
Video resolutions Min = 1920х1080, Max = 3840х2160
Video duration 4 second
Number of background 9
Video overlap No more than 5%
Devices IOS, Android
Source and collection methodology. Data was collected by a partner of Unidata.

Dataset Use Cases

  • Biometric Security

    Enhancing Spoof Detection Systems

    Printed 2D Masks Attacks Dataset provides facial images with printed masks and print attacks, helping researchers improve facial recognition systems. The dataset includes files containing human faces under varied conditions, offering training data for recognition algorithms that distinguish between real faces and 2D printed imitations.

  • Financial Services

    Preventing Fraud in Identity Verification

    Banks and fintech platforms use this masks dataset to strengthen biometric authentication against printed photos and 2D mask attacks. By training models on datasets containing segmentation masks and facial images, institutions can reduce fraud risks in KYC processes and ensure more secure identity verification systems.

  • Healthcare & Access Control

    Protecting Medical Systems from Spoofing

    In hospitals and clinics, facial recognition supports secure access to sensitive medical data. Our Printed 2D Masks Dataset supplies training data with printed masks and facial images, enabling the development of trained models that detect spoofing attempts, safeguarding medical images and patient records from unauthorized access.

  • Certification & Compliance

    Supporting iBeta Level 1 & 2 Testing

    This Unidata dataset provides over 4,800 videos of people wearing or holding 2D printed masks, making it valuable for fraud prevention and presentation attack detection. It helps developers prepare facial recognition and liveness detection systems for iBeta Level 1 and Level 2 certification, ensuring compliance with industry standards.

FAQs

What does Printed 2D Masks Attacks Dataset include?
It includes more than 4,800 videos of individuals wearing or holding printed 2D masks. Each video contains metadata such as age, gender, ethnicity, and recording device, supporting detailed facial recognition testing.
What types of annotations are provided?
Annotations include metadata labels with 31 attributes such as demographic information and device type. This makes the dataset suitable for building trained models that identify 2D mask attacks and detect unsafe biometric practices.
How was the dataset collected?
The dataset was recorded using both iOS and Android devices in different conditions. Videos were collected across 9 backgrounds with resolutions ranging from 1920×1080 to 3840×2160, ensuring high-quality training data for recognition tasks. The Masks Biometric Attacks Dataset was created using real participants performing 2D printed mask attacks under multiple conditions.
What video formats and durations are provided?
The dataset is delivered in MP4 and MOV formats, with each video lasting around 4 seconds. This consistent length makes it easier to use in training datasets and recognition technology benchmarks.
How are Unidata datasets licensed?
Unidata datasets follow a dual-licensing model designed to support both research and commercial applications. Free samples of Printed 2D Masks Attacks Dataset are provided for trial and testing, while full access to the dataset is available exclusively after purchase.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All Unidata datasets are created in full compliance with GDPR and relevant international data protection regulations. This dataset is compiled from legally sourced data, ensuring ethical collection, lawful processing, and responsible use in facial recognition and anti-spoofing research.
How are Unidata datasets stored?
Unidata securely stores all datasets, including Printed 2D Masks Attacks Dataset, on AWS cloud infrastructure for maximum reliability and security. Storage and management procedures meet ISO 27001 and ISO 27701 standards, ensuring that data integrity, availability, and privacy are maintained across all facial recognition and biometric datasets.
How long does it take to receive the dataset?
After submitting a dataset request, our team will review the details, finalize documentation, and provide a purchase agreement. Once payment is completed, a dataset is typically delivered within 3–10 business days.
Still have questions about using Unidata datasets? Read our user-guides

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