This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Motion estimation (ME) methods based on differential techniques provide useful information for video analysis, and moreover it is relatively easy to embed into them regularity con...
Marco Cagnazzo, Wided Miled, Thomas Maugey, B&eacu...
Reliable estimation of visual saliency allows appropriate processing of images without prior knowledge of their content, and thus remains an important step in many computer vision ...
Ming-Ming Cheng, Guo-Xin Zhang, Niloy J. Mitra, Xi...
Non-rigid structure from motion (NRSFM) is a difficult, underconstrained problem in computer vision. The standard approach in NRSFM constrains 3D shape deformation using a linear...
In this paper, we propose a bilevel sparse coding model for coupled feature spaces, where we aim to learn dictionaries for sparse modeling in both spaces while enforcing some desi...