In this work we introduce a novel approach to object categorization that incorporates two types of context ? cooccurrence and relative location ? with local appearancebased featur...
Carolina Galleguillos, Andrew Rabinovich, Serge Be...
A popular view is that the brain works in a similar way to a digital computer or a Universal Turing Machine by processing symbols. Psychophysical experiments and our amazing capabi...
Flat appearance-based systems, which combine clever image representations with standard classifiers, might be the most effective way to recognize objects using current technologie...
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
This paper describes an efficient approach to image annotation. It ranked first on the recent scene categorization track of the ImagEVAL1 benchmark. We show how homogeneous globa...