Given a single RGB image our goal is to label every pixel with an affordance type. By affordance, we mean an object’s capability to readily support a certain human action, without requiring precursor actions. We focus on segmenting the following five affordance types in indoor scenes: ‘walkable’, ‘sittable’, ‘lyable’, ‘reachable’, and ‘movable’. Our approach uses a deep architecture, consisting...