Study of real time face recognition using few shot recognition techniques

This paper aims at studying the problem of face recognition using very few examples. Face recognition is a tough problem yet is important for several practical applications. Contemporary techniques require thousands of samples to recognize them effectively. However, constructing such a dataset is not always feasible for practical applications. Therefore, we analyze the effectiveness of such techniques with few shot learning paradigms on benchmark datasets with standard evaluation metrics.