We present a method to learn object class models from unlabeled and unsegmented cluttered scenes for the purpose of visual object recognition. We focus on a particular type of mode...
In this paper, a new information extraction system by statistical shallow parsing in unconstrained handwritten documents is introduced. Unlike classical approaches found in the li...
Simon Thomas, Clement Chatelain, Laurent Heutte, T...
In this paper, we describe a nonlinear image representation based on divisive normalization that is designed to match the statistical properties of photographic images, as well as...
The algorithm presented in this paper aims to segment the foreground objects in video (e.g., people) given timevarying, textured backgrounds. Examples of time-varying backgrounds ...
We demonstrate a novel method for producing a synthetic talking head. The method is based on earlier work in which the behaviour of a synthetic individual is generated by referenc...