Recently, the optimal distance measure for a given object discrimination task under the nearest neighbor framework was derived [1]. For ease of implementation and efficiency consi...
We address the task of learning a semantic segmentation from weakly supervised data. Our aim is to devise a system that predicts an object label for each pixel by making use of on...
We present an approach to visual object-class recognition and segmentation based on a pipeline that combines multiple, holistic figure-ground hypotheses generated in a bottom-up,...
Kernel methods provide an efficient mechanism to derive nonlinear algorithms. In classification problems as well as in feature extraction, kernel-based approaches map the original...
We seek to recognize the place depicted in a query image using a database of “street side” images annotated with geolocation information. This is a challenging task due to chan...