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DATASET
Spoof attacks with printed selfies of people of different genders, ages and ethnicities. The dataset effectively solves security problems for biometric identification systems.
Anti-spoofing
Printed photo
The ability to recognize and analyze images and videos
Computer Vision
A way to identify or confirm a person's identity by his face
Face recognition
Identification and verification of the client by financial and other institutions
Know Your Cutomer
Methods of preventing deception of identification systems
Anti-spoofing
Liveness Detection
Checks whether the system interacts with a living person
10 000
spoof attacks
10-15
seconds each video
9.41
usability
Technical
specifications:
specifications:
Each dataset set includes: a photo, a video of a person and a video of an attack with a printed photo.
Photo - a selfie of a person from a mobile phone, a person is depicted on it alone, the face is clearly visible.
Technical
specifications:
specifications:
Each dataset set includes: a photo, a video of a person and a video of an attack with a printed photo.
Video - shot on the front camera, on it a person alternately moves his head left, right, up and down.
Technical
specifications:
specifications:
Each dataset set includes: a photo, a video of a person and a video of an attack with a printed photo.
Video of the attack - a person takes a printed photo on video for 10-15 seconds
Metadata in the cvc format is prepared for each media file:
Race
Country of residence
Age
Gender
The device from which the picture was taken
Extra Services
● Data collection of photos and videos by required attributes and metadata: frame rate, image resolution, demographic and geographical characteristics
● Collecting photos and videos of attacks from MacBook, iPad and iPhone webcams
● Collecting videos from printed photos on different paper (plain, matte, glossy) with a length of 5 seconds to 3 minutes
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