This paper explores correspondence and mixture topic modeling of documents tagged from two different perspectives. There has been ongoing work in topic modeling of documents with...
We introduce a new technique that can reduce any
higher-order Markov random field with binary labels into
a first-order one that has the same minima as the original.
Moreover, w...
We present a method to learn visual attributes (eg.“red”,
“metal”, “spotted”) and object classes (eg. “car”,
“dress”, “umbrella”) together. We assume imag...
We propose a novel framework for contour based object
detection and recognition, which we formulate as a joint
contour fragment grouping and labeling problem. For a
given set of...
ChengEn Lu, Longin Jan Latecki, Nagesh Adluru, Hai...
In this paper we propose to use lexical semantic networks to extend the state-of-the-art object recognition techniques. We use the semantics of image labels to integrate prior kno...