In this paper we introduce and exploit the concept of contextual rules in the field of object detection. These rules are defined as associations between different object likelihoo...
Mutual Boosting is a method aimed at incorporating contextual information to augment object detection. When multiple detectors of objects and parts are trained in parallel using A...
The context-centered approach to object detection and recognition is based on the intuition that the contextual information of real-world scenes provides relevant information for ...
We study the problem of object classification when training
and test classes are disjoint, i.e. no training examples of
the target classes are available. This setup has hardly be...
Christoph H. Lampert, Hannes Nickisch, Stefan Harm...
Object class models trained on hundreds or thousands of
images have shown to enable robust detection. Transferring
knowledge from such models to new object classes trained
from ...