This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...
It is a common human behavior to hold a small object of interest and to manipulate it for observation. A computer system, symbiotic with a human, should recognize the object and th...
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 presents a method for accurately segmenting moving container trucks in image sequences. This task allows to increase the performance of a recognition system that must id...
A general-purpose object indexingtechnique is described that combines the virtues of principal component analysis with the favorable matching properties of high-dimensional spaces...