We address the problem of recovering 3D human pose from single 2D images, in which the pose estimation problem is formulated as a direct nonlinear regression from image observation...
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
We present a unified framework for reasoning about worst-case regret bounds for learning algorithms. This framework is based on the theory of duality of convex functions. It brin...
A human annotator can provide hints to a machine learner by highlighting contextual "rationales" for each of his or her annotations (Zaidan et al., 2007). How can one ex...
We consider the problem of grasping novel objects, specifically ones that are being seen for the first time through vision. Grasping a previously unknown object, one for which a 3...