Although the ability to recognize faces and objects from a variety of viewpoints is crucial to
our everyday behavior, the underlying cortical mechanisms are not well understood …

Metric learning constitutes a well-investigated field for vectorial data with successful
applications, eg in computer vision, information retrieval, or bioinformatics. One particularly …

The way we perceive an object depends both on feedforward, bottom-up processing of its
physical stimulus properties and on top-down factors such as attention, context, expectation …

Robots that share their environment with humans need to be able to recognize and
manipulate objects and users, perform complex navigation tasks, and interpret and react to …

The continuous rise in the number of vehicles in circulation brings an increasing need for
automatically and efficiently recognizing vehicle categories for multiple applications such as …

This paper investigates a novel solution for the recognition of objects of interest in aerial
images. The solution builds on a combination of algorithms inspired from the human visual …

From its early beginnings to today, the interdisciplinary endeavor of cognitive science has
led to a fundamentally improved understanding of many aspects of cognition. Some of this is …

Contextual information can greatly improve both the speed and accuracy of object
recognition. Context is most often viewed as a static concept, learned from large image …

Understanding visual attention is a long-term goal in the field of neuroscience, and a
prerequisite to incorporate this essential concept of human perception into computer vision …

Real-time interaction in virtual environments composed of numerous objects modeled with a
high number of faces remains an important issue in interactive virtual environment …