no code implementations • ICCV 2017 • Nasim Souly, Concetto Spampinato, Mubarak Shah
Semantic segmentation has been a long standing challenging task in computer vision.
no code implementations • 28 Mar 2017 • Nasim Souly, Concetto Spampinato, Mubarak Shah
Semantic segmentation has been a long standing challenging task in computer vision.
2 code implementations • CVPR 2017 • Concetto Spampinato, Simone Palazzo, Isaak Kavasidis, Daniela Giordano, Mubarak Shah, Nasim Souly
In particular, we employ EEG data evoked by visual object stimuli combined with Recurrent Neural Networks (RNN) to learn a discriminative brain activity manifold of visual categories.
no code implementations • 17 Aug 2016 • Nasim Souly, Mubarak Shah
In this paper, we propose to use high-level knowledge regarding rules in the inference to incorporate dependencies among regions in the image to improve scores of classification.
no code implementations • 16 Jun 2016 • Subhabrata Bhattacharya, Nasim Souly, Mubarak Shah
Using an over-complete dictionary of the covariance based descriptors built from labeled training samples, we formulate low-level event recognition as a sparse linear approximation problem.
no code implementations • CVPR 2016 • Nasim Souly, Mubarak Shah
To do this, we formulate the problem as an energy minimization over a graph, whose structure is captured by applying sparse constraint on the elements of the precision matrix.