: This paper addresses the inference of probabilistic classification models using weakly supervised learning. The main contribution of this work is the development of learning meth...
Recognizing object classes and their 3D viewpoints is an
important problem in computer vision. Based on a partbased
probabilistic representation [31], we propose a new
3D object...
Given a set of images of scenes containing multiple object categories (e.g. grass, roads, buildings) our objective is to discover these objects in each image in an unsupervised man...
This paper describes a new approach to combine multiple modalities and applies it to the problem of affect recognition. The problem is posed as a combination of classifiers in a p...
This article presents a method aiming at quantifying the visual similarity between an image and a class model. This kind of problem is recurrent in many applications such as objec...