We propose an approach for learning visual models of object categories in an unsupervised manner in which we first build a large-scale complex network which captures the interacti...
We propose a spectral partitioning approach for large-scale optimization problems, specifically structure from motion. In structure from motion, partitioning methods reduce the pr...
The number of features that can be computed over an image is, for practical purposes, limitless. Unfortunately, the number of features that can be computed and exploited by most c...
We present a variational integration of nonlinear shape statistics into a Mumford?Shah based segmentation process. The nonlinear statistics are derived from a set of training silho...
In this work we present a method to jointly separate active audio and visual structures on a given mixture. Blind Audiovisual Source Separation is achieved exploiting the coherenc...
Anna Llagostera Casanovas, Gianluca Monaci, Pierre...