This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the b...
Pedro F. Felzenszwalb, David A. McAllester, Deva R...
Abstract. In this paper we investigate a new method of learning partbased models for visual object recognition, from training data that only provides information about class member...
Grouping and Abstraction Using Simple Part Models Pablo Sala and Sven Dickinson Department of Computer Science, University of Toronto, Toronto ON, Canada We address the problem of ...
We introduce a general model of refinement. This is defined in terms of what contexts an entity can appear in, and what observations can be made of it in those contexts. We show e...
This paper proposes a method for predicting the complexity of meshing Computer Aided Design (CAD) geometries with unstructured, hexahedral, finite elements. Meshing complexity ref...