In this paper, we present a novel framework for constructing large deformation log-unbiased image registration models that generate theoretically and intuitively correct deformati...
Igor Yanovsky, Paul M. Thompson, Stanley Osher, Al...
In this paper we present a novel method for parsing aerial images with a hierarchical and contextual model learned in a statistical framework. We learn hierarchies at the scene an...
Jake Porway, Kristy Wang, Benjamin Yao, Song Chun ...
In this paper, we address the pair-activity classification problem, which explores the relationship between two active objects based on their motion information. Our contributions...
Most successful object recognition systems rely on binary classification, deciding only if an object is present or not, but not providing information on the actual object location...
Christoph H. Lampert, Matthew B. Blaschko, Thomas ...
This paper presents a new approach to discriminative modeling for classi cation and labeling. Our method, called Boosting on Multilevel Aggregates (BMA), adds a new class of hiera...