A variety of flexible models have been proposed to detect
objects in challenging real world scenes. Motivated
by some of the most successful techniques, we propose a
hierarchica...
Paul Schnitzspan (TU Darmstadt), Mario Fritz (Univ...
We present a generic objectness measure, quantifying how
likely it is for an image window to contain an object of
any class. We explicitly train it to distinguish objects with
a...
Pierre America, Robin Milner, Oscar Nierstrasz, Ma...
Software available at http://disi.unitn.it/~uijlings or http://koen.me/research/
For object recognition, the current state-of-the-art is based on exhaustive search. However, to ...
We present a hierarchical classification model that allows rare objects to borrow statistical strength from related objects that have many training examples. Unlike many of the e...
Ruslan Salakhutdinov, Antonio Torralba, Josh Tenen...
We consider the problem of visual categorization with minimal supervision during training. We propose a partbased model that loosely captures structural information. We represent ...