CRITICAL ANALYSIS OF SELF-SUPERVISION

Presented by

Maral Rasoolijaberi

Introduction

This paper aims to learn the deep features of CNNs without manual labels by using supervision techniques. The main idea of self-supervision approaches is to learn from unlabeled data and pre-train networks via pretext tasks that can be automatically generated from the data itself.