Sparse methods for supervised learning aim at finding good linear predictors from as few variables as possible, i.e., with small cardinality of their supports. This combinatorial ...
We develop a method for generating smooth trajectories for a set of mobile robots. Given two end configurations, by tuning one parameter, the user can choose an interpolating tra...
Abstract We present the first method to handle curvature regularity in region-based image segmentation and inpainting that is independent of initialization. To this end we start f...
Thomas Schoenemann, Fredrik Kahl, Simon Masnou, Da...
We consider an interactive browsing environment, with greedy optimization of a current view, conditioned on the availability of previously transmitted information for other (possi...
Pietro Zanuttigh, Nicola Brusco, David Taubman, Gu...
In this paper, we rely on the theory of marked point processes to perform an unsupervised road network extraction from optical and radar images. A road network is modeled by a Mar...