System and method for performing face recognition

A method of training an ML model to recognize a face, the method comprising:

• receiving a first image depicting a first face;
• obtaining a distinctiveness map, associating a distinctiveness score to one or more regions in the first face;
• selecting one or more regions of the first face, that are associated with a distinctiveness score that is higher than the lowest distinctiveness score, based on the distinctiveness map;
• performing one or more modifications of the selected one or more regions of the first image, to produce one or more modified images;
• and
• training the ML model to recognize the depicted face, using the one or more modified images as a training dataset, and using the first image as supervisory data.

A method of performing face recognition by at least one processor, the method comprising:

• receiving a first facial image, depicting a first face, and a second facial image depicting a second face;
• applying an ML model on the first image, to produce a first representation vector, and applying the ML model on the second image to produce a second representation vector;
• comparing the first representation vector and the second representation vector;
• and associating the first face with the second face based on the comparison, wherein the ML model is trained to produce the representation vectors from the facial images, based on regions in the facial images that correspond to distinctiveness scores that are beneath a distinctiveness threshold.