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Aurora Guard Face Dataset – 419 Participants, Colorful Liveness Detection
colorful face dataset
aurora guard liveness dataset
face anti-spoofing aurora guard
multi-light face recognition dataset
biometric authentication face dataset
remote ID face dataset
real vs fake face detection dataset
AI face recognition training data
This aurora guard face dataset contains 419 participants with diverse ages and genders, the collection scenes include indoor and outdoor scenes. Devices include cellphone and Pad. The data includes various devices, various anti-spoofing samples, multiple light conditions, multiple scenes. This dataset is ideal for training face recognition, biometric authentication, and remote ID verification models in multi-light, multi-scene environments.
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Specifications
Data size
419 people, 11 people were 3D head models or 3D facial masks data, which were collected by 2-3 people wearing masks, and no subsequent data statistics were conducted
Population distribution
Race distribution: Asian; Gender distribution: 204 males, 204 females; Age distribution: 40 people under 18 years old, 258 people aged from 18 to 45, 73 people aged from 46 to 60, 37 people over 60 years old
Collecting environment
248 people in indoor scenes, 160 people in outdoor scenes
Data diversity
various devices, various anti-spoofing samples, multiple light conditions, multiple scenes
Device
cellphone, Pad
Data format
.mp4
Annotation content:
label the person – ID, race, gender, age, collecting scene, glasses state, light condition
Accuracy
based on the accuracy of the actions, the accuracy exceeds 97%; the accuracy of label annotation is not less than 97%
Specifications
Sample
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