Datasets:
license: cc-by-nd-4.0
task_categories:
- image-to-image
- video-classification
language:
- en
tags:
- ibeta
- liveness detection
- biometric
- anti-spoofing
size_categories:
- 10K<n<100K
Printed Photos Attacks - liveness detection dataset
The anti spoofing dataset comprises videos of genuine facial presentations using printed 2D photos, as well as real and spoof faces. It proposes a novel approach that learns and extracts facial features to prevent spoofing attacks, based on deep neural networks and advanced biometric techniques.
Our results show that this technology works effectively in securing most applications and prevents unauthorized access by distinguishing between genuine and spoofed inputs. Additionally, it addresses the challenging task of identifying unseen spoofing cues, making it one of the most effective techniques in the field of anti-spoofing research.
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Content
The dataset contains of three folders:
- live_selfie contains the original selfies of people
- live_video includes original videos of people
- attack contains videos of attacks with printed photos with the original images from "live_selfie" folder
File with the extension .csv
includes the following information for each media file:
- live_selfie: the link to access the original selfie
- live_video: the link to access the original video
- attack: the link to access the video of attack with the printed photo
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