2D Masks Attack for facial recogniton system

The dataset consists of 4,800+ videos of people wearing of holding 2D printed masks filmed using 5 devices. It is designed for liveness detection algorithms, specifically aimed at enhancing anti-spoofing capabilities in biometric security systems.

By leveraging this dataset, researchers can create more sophisticated recognition system, crucial for achieving iBeta Level 1 & 2 certification – a key standard for secure and reliable biometric systems designed to combat spoofing and 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 2D printed 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

Variables in .csv files:

name: filename of the printed 2D mask
path: link-path for the original video
type: type(wearing or holding) of printed mask

Researchers are developing advanced anti-spoofing detection techniques to enhance security systems against attacks using face masks.This focus on face masks allows researchers to train and test detection algorithms specifically designed to differentiate between genuine human faces and these increasingly sophisticated mask-based spoofing attempts.

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