The goal of our work is object categorization in real-world scenes. That is, given a novel image we want to recognize and localize unseen-before objects based on their similarity t...
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
Abstract. Humans have the remarkable ability to generalize from binocular to monocular figure-ground segmentation of complex scenes. This is clearly evident anytime we look at a p...
Brian Mingus, Trent Kriete, Seth A. Herd, Dean Wya...
— We propose a learning algorithm for estimating the 3-D orientation of objects. Orientation learning is a difficult problem because the space of orientations is non-Euclidean, ...
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...