0
$\begingroup$

I am newbie in face recognition related things... As far i observed dlib's frontal_face_detectoris widely used to find the faces in an image and after that, to extract face_descriptor vectors which is better for real time face authentication system ?

It looks both working fine.. but in real-time implementation,

  • Is there some thing important to understand the performance ?

  • Or any comparison checks done on real time / large data sets ?

    Thanks in advance.

$\endgroup$
0
$\begingroup$

In my experience with the natively LR, tinyface dataset, dlib's resnetv1 model failed to extract embeddings for a number of faces from images with high gaussian blur. However, FaceNet was able to vectorize those same poor-quality LR images.

$\endgroup$

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.