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...
Context is critical for minimising ambiguity in object de-
tection. In this work, a novel context modelling framework
is proposed without the need of any prior scene segmen-
tat...
We develop a multi-class object detection framework whose core component is a nearest neighbor search over object part classes. The performance of the overall system is critically...
We propose an approach for detecting objects in large-scale range datasets that combines bottom-up and top-down processes. In the bottom-up stage, fast-to-compute local descriptors...
Alexander Patterson, Philippos Mordohai, Kostas Da...
For detecting objects in natural visual scenes, several powerful image features have been proposed which can collectively be described as spatial histograms of oriented energy. Th...