UniDataPro/latex-mask-attack

Face mask dataset for facial recognition

This dataset contains over 11,100+ video recordings of people wearing latex masks, captured using 5 different devices.It is designed for liveness detection algorithms, specifically aimed at enhancing anti-spoofing capabilities in biometric security systems.

By utilizing this dataset, researchers can develop more accurate facial recognition technologies, which is crucial for achieving the iBeta Level 2 certification, a benchmark for robust and reliable biometric systems that prevent fraud. - Get the data

Attacks in the dataset

The attacks were recorded in diverse settings, showcasing individuals with various attributes. Each video includes human faces adorned with latex masks to mimic potential spoofing attempts in facial recognition systems.

Variants of backgrounds and attributes in the dataset:

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Metadata for the dataset

The dataset focuses on developing robust detection algorithms to accurately identify latex masks during mask detection processes.It can help improve liveness detection systems, which are independently certified by iBeta, an independent laboratory that assesses the reliability of these systems.

Frequently Asked Questions

How many backgrounds are represented?

The videos were recorded across nine different backgrounds, introducing environmental variation into the dataset. This can help you determine whether a spoofing detector is learning characteristics of the latex mask itself or relying on contextual cues from a particular environment.

What video resolutions are available?

The collection contains high-resolution videos ranging from 1920 × 1080 to 3840 × 2160 pixels. The availability of both Full HD and 4K footage gives you flexibility when designing facial recognition and anti-spoofing experiments.

Can the dataset be used for iBeta Level 2-related development?

Yes. The collection is designed to support development of biometric anti-spoofing systems and iBeta Level 2 certification-related work, particularly for physical latex-mask attacks. You can use the videos to train or stress-test presentation attack detection models and identify weaknesses against realistic 3D facial masks. However, using the dataset does not itself provide iBeta certification or guarantee compliance with a certification test.

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