Face Anti-Spoofing feature enables to prevent false facial verification by using a photo, video or a different substitute for an authorized person’s face.
This model can defend against video attacks which is a sophisticated way to trick the face recognition systems, usually requiring a looped video of a victim’s face.
This model can be used for client authentication.
It can be an ideal complement to facial recognition systems.
2 class: (spoof; real)
mAP (mean average precision):
class_id = 0, name = Spoof, ap = 99.33%
class_id = 1, name = Real, ap = 99.41%
for conf_thresh = 0.25, precision = 0.96, recall = 0.98, F1-score = 0.97
for conf_thresh = 0.25, average IoU = 85.73 %
IoU threshold = 50 %, used Area-Under-Curve for each unique Recall
mean average precision (mAP@0.50) = 0.993667, or 99.37 %
Inference time using CPU: 300 ms (on HP Laptop 15-DA0042NH (Processor: Intel(R) Core(TM) i7-8550U CPU))