UniqueData/display-spoof-attack

Liveness Detection - Video Classification

The dataset is created on the basis of 2D Printed Mask and Replay Attack Videos Dataset

The biometric attack dataset with replay attacks on the real videos of people. Replay attack involves presenting a pre-recorded video or previously captured footage as if it were occurring in real-time. The primary objective is to distinguish between genuine, real-time footage and manipulated recordings.

The videos were gathered by capturing faces of genuine individuals presenting spoofs, using facial presentations. Our dataset proposes a novel approach that learns and detects spoofing techniques, extracting features from the genuine facial images to prevent the capturing of such information by fake users.

The dataset contains videos of real humans with various resolutions, views, and colors, making it a comprehensive resource for researchers working on anti-spoofing technologies.

The dataset provides data to combine and apply different techniques, approaches, and models to address the challenging task of distinguishing between genuine and spoofed inputs, providing effective anti-spoofing solutions in active authentication systems. These solutions are crucial as newer devices, such as phones, have become vulnerable to spoofing attacks due to the availability of technologies that can create replays, reflections, and depths, making them susceptible to spoofing and generalization.

People in the dataset

Our dataset also explores the use of neural architectures, such as deep neural networks, to facilitate the identification of distinguishing patterns and textures in different regions of the face, increasing the accuracy and generalizability of the anti-spoofing models.

💴 For Commercial Usage: Full version of the dataset includes 110,000+ photos of people, leave a request on our website to buy the dataset

Metadata for the full dataset:

• replay.assignment_id - unique identifier of the media file
• real_assignment_id- unique identifier of the media file from the Antispoofing Real Dataset
• worker_id - unique identifier of the person
• age - age of the person
• true_gender - gender of the person
• country - country of the person
• ethnicity - ethnicity of the person
• video_extension - video extensions in the dataset
• video_resolution - video resolution in the dataset
• video_duration - video duration in the dataset
• video_fps - frames per second for video in the dataset

💴 Buy the Dataset: This is just an example of the data. Leave a request on the our website to discuss your requirements, learn about the price and buy the dataset

Content

The dataset includes files folder with videos of people

File with the extension .csv

• id: id of the person,
• file: link to access the display spoof attack video

Get the dataset

This is just an example of the data

Leave a request on our website to discuss your requirements, learn about the price and buy the dataset.

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