The Illustrated SimCLR Framework

In recent years, numerous self-supervised learning methods have been proposed for learning image representations, each getting better than the previous. But, their performance was still below the supervised counterparts. This changed when Chen et. The SimCLR paper not only improves upon the previous state-of-the-art self-supervised learning methods but also beats the supervised learning method on ImageNet classification when scaling up the architecture. In this article, I will explain the key ideas of the framework proposed in the research paper using diagrams.