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...
Abstract. We present a biologically inspired vision system able to incrementally learn multiple visual categories by interactively presenting several hand-held objects. The overall...
Stephan Kirstein, Heiko Wersing, Horst-Michael Gro...
In this paper we propose a method for continuous learning of simple visual concepts. The method continuously associates words describing observed scenes with automatically extracte...
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
A key ingredient in the design of visual object classification
systems is the identification of relevant class specific
aspects while being robust to intra-class variations. Whil...