I'm very familiar with the BlazeFace and FaceMesh models (which are related to this in Google's MediaPipe framework).
They have weaknesses - they aren't designed for running upside down for example, so if they get data that is that way oriented they will tend to fail.
They aren't designed for "life" detection, so you can show printed pictures of a face and it will detected it.
But they give you confidence scores etc, so if you give it something like a caricature of a face it will return reasonable confidence numbers indicating it isn't as sure of its predictions.
I'm very familiar with the BlazeFace and FaceMesh models (which are related to this in Google's MediaPipe framework).
They have weaknesses - they aren't designed for running upside down for example, so if they get data that is that way oriented they will tend to fail.
They aren't designed for "life" detection, so you can show printed pictures of a face and it will detected it.
But they give you confidence scores etc, so if you give it something like a caricature of a face it will return reasonable confidence numbers indicating it isn't as sure of its predictions.