We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
A new approach to tracking weakly modeled objects in a semantically rich domain is presented. We define a closed-world as a space-time region of an image sequence in which the co...
We describe our experiments using the DeSR parser in the multilingual and domain adaptation tracks of the CoNLL 2007 shared task. DeSR implements an incremental deterministic Shif...
Giuseppe Attardi, Felice dell'Orletta, Maria Simi,...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
In this paper, we address the problem of estimating the 3D structure and motion of a deformable object given a set of image features tracked automatically throughout a video seque...
Alessio Del Bue, Fabrizio Smeraldi, Lourdes de Aga...