We propose a new technique for fusing multiple cues to robustly segment an object from its background in video sequences that suffer from abrupt changes of both illumination and p...
Francesc Moreno-Noguer, Alberto Sanfeliu, Dimitris...
We present a probabilistic framework for recognizing objects in images of cluttered scenes. Hundreds of objects may be considered and searched in parallel. Each object is learned f...
—In this work, we make use of 3D visual contours carrying geometric as well as appearance information. Between these contours, we define 3D relations that encode structural info...
Emre Baseski, Leon Bodenhagen, Nicolas Pugeault, S...
We propose a novel probabilistic framework for learning
visual models of 3D object categories by combining appearance
information and geometric constraints. Objects are
represen...
A key ingredient in the design of visual object classification
systems is the identification of relevant class specific
aspects while being robust to intra-class variations. Whil...