Which is best FaceNet or dlib_face_recognition_resnet_model_v1? 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 ?

FaceNet by google
dlib_face_recognition_resnet_model_v1 by face_recognition

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.
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.