Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the dis...
We propose a new approach to collision and self– collision detection of dynamically deforming objects that consist of tetrahedrons. Tetrahedral meshes are commonly used to repre...
Matthias Teschner, Bruno Heidelberger, Matthias M&...
This paper presents an empirical evaluation of the role of
context in a contemporary, challenging object detection task
– the PASCAL VOC 2008. Previous experiments with context...
Alexei A. Efros, Derek Hoiem, James Hays, Martial ...
A key goal of far-field activity analysis is to learn the usual pattern of activity in a scene and to detect statistically anomalous behavior. We propose a method for unsupervised...
In this work a framework for constructing object detection classifiers using weakly annotated social data is proposed. Social information is combined with computer vision techniq...