Here we explore a discriminative learning method on underlying generative models for the purpose of discriminating between object categories. Visual recognition algorithms learn m...
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
For object category recognition to scale beyond a small number of classes, it is important that algorithms be able to learn from a small amount of labeled data per additional clas...
Kevin Tang, Marshall Tappen, Rahul Sukthankar, Chr...
We propose to shift the goal of recognition from naming
to describing. Doing so allows us not only to name familiar
objects, but also: to report unusual aspects of a familiar
ob...
Ali Farhadi, David A. Forsyth, Derek Hoiem, Ian En...
Graph construction plays a key role on learning algorithms based on graph Laplacian. However, the traditional graph construction approaches of -neighborhood and k-nearest-neighbor...