What does the Latex Mask Attack dataset include?

The dataset contains 11,100+ high-resolution videos of individuals wearing latex masks, specifically curated for training face anti-spoofing and liveness detection models.

How can this dataset be used in AI and machine learning?

It is ideal for building and testing biometric authentication systems, spoof detection models, computer vision algorithms, and real-time liveness detection solutions.

Does the dataset include diversity in age, ethnicity, and regions?

Yes, the dataset is collected from diverse age groups, ethnic backgrounds, and multiple geographic regions to help improve model generalization and reduce bias.

Are annotation and labeling services available?

GTS offers frame-level labels, spoof-type tagging, mask characteristics, action labels, and customizable annotation workflows based on project requirements.

How does GTS ensure dataset quality and compliance?

All datasets undergo multi-stage QC validation and follow GDPR, HIPAA, and ISO 9001/27001-certified processes to ensure accuracy, security, and ethical data handling.

Can this dataset be customized or scaled for large projects?

Yes, GTS can collect and annotate custom mask, spoof, and identity datasets at large scale with a trained global workforce and secure infrastructure.

Latex Mask Attack - 11,100+ videos

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Latex Mask Attack - 11,100+ videos

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Latex Mask Attack - 11,100+ videos

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Latex Mask Attack - 11,100+ videos

Description

Explore the Face Mask Dataset with 11,100+ video recordings of latex mask-wearing individuals, designed to enhance liveness detection and anti-spoofing in facial recognition systems.

Description:

Access the Face Mask Dataset with 11,100+ video recordings of individuals wearing latex masks, designed for liveness detection and anti-spoofing in facial recognition systems. Ideal for developing secure biometric security solutions and achieving iBeta Level 2 certification.

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The Face Mask Dataset for Facial Recognition contains over 11,100 video recordings of individuals wearing latex masks, captured across 5 different devices. This dataset is specifically designed for developing liveness detection algorithms aimed at improving anti-spoofing capabilities in biometric security systems.

Key Features of the Dataset:

11,100+ Video Recordings: A large collection of videos featuring individuals wearing latex masks to simulate spoofing attacks on facial recognition systems.
Diverse Settings and Subjects: The videos showcase various environments and individuals with different attributes, ensuring real-world applicability and diversity.
Multiple Devices: Captured using 5 different devices, enhancing the robustness of facial recognition models across different hardware.
Liveness Detection Focus: The dataset is intended for improving liveness detection, which is crucial for preventing fraud and ensuring secure biometric authentication.

This dataset is sourced from Kaggle.

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Latex Mask Attack - 11,100+ videos