The Visual Learning Group researches methods to learn models of the real-world from images and video. Our most recent work leverages the framework of deep learning to address challenging problems at the boundary between computer vision and machine learning. Projects include image categorization, action recognition, depth estimation from single photo, as well as 3D reconstruction of human movement from monocular video.