In this paper, we propose a machine learning approach to title extraction from general documents. By general documents, we mean documents that can belong to any one of a number of...
Yunhua Hu, Hang Li, Yunbo Cao, Dmitriy Meyerzon, Q...
The ability to normalize pose based on super-category landmarks can significantly improve models of individual categories when training data are limited. Previous methods have co...
We describe a method for learning steerable deformable part models. Our models exploit the fact that part templates can be written as linear filter banks. We demonstrate that one...
In this paper, we present the LIP6 annotation models for the ImageCLEFannotation 2010 task. We study two methods to train and merge the results of different classifiers in order to...
Ali Fakeri-Tabrizi, Sabrina Tollari, Nicolas Usuni...
Image auto-annotation is an important open problem in
computer vision. For this task we propose TagProp, a discriminatively
trained nearest neighbor model. Tags of test
images a...
Matthieu Guillaumin, Thomas Mensink, Jakob Verbeek...