In this talk, we will explore the problem of learning the 2D geometry of object categories from unlabelled images or videos. Specifically, I will introduce our novel method that learns to discover object landmarks without any manual annotations. It automatically learns from images or videos and works across different datasets of faces, humans, and animals. I will also show how a weak empirical prior can be incorporated into the method in order to learn human-interpretable landmarks.