Self-Supervised Learning and the Quest for Reducing Labeled Data in Deep Learning

There is one single thing that every Deep Learning practitioner agrees. Deep learning models are data inefficient. Let's start by considering the popular task of classification in Computer Vision. Take the ImageNet database as an example. It contains 1.3 million images from 1000 different classes.