Event Location: NSH 1305
Bio: Derek Hoiem is a new assistant professor at University of Illinois at Urbana
Champaign. Derek researches object recognition, segmentation, 3d
reconstruction from images, and other aspects of computer vision that are
related to scene understanding. He recently (2007) graduated from the
Robotics Institute under the tutelage of Alyosha Efros and Martial Hebert
and looks forward to visiting. By request, Derek will share a little of his
perspective in transitioning from being a grad student at CMU to a professor
at UIUC.

Abstract: Ultimately, the goal of computer vision is to make useful inferences from
imagery, and a big part of that is knowing something about the properties of
nearby objects. In this talk, I’ll describe our recent work on learning to
identify object attributes, such as parts, materials, or shape, from images
in a way that generalizes to new object categories. The tricky part is
training classifiers that really predict the intended attribute, and not
ones that are correlated through familiar object categories. Once we can
predict attributes, we can say what is unusual about an object and more
easily learn to recognize new objects. Sometimes we can even recognize new
object categories from a purely verbal description (e.g., a goat has four
legs, horns, and is furry).

This work is with Ali Farhadi, Ian Endres, and David Forsyth at UIUC.