Abstract: This talk describes work on detecting and parsing humans into joints and semantic parts. It combines deep networks with graphical models for reasoning about the spatial relations between joints. We discuss methods for dealing with occlusion and scale variations. Finally we describe compositional methods for extracting key-point motifs for classifying human actions.