Training a generic objectness measure to produce a small set of candidate object windows, has been shown to speed up the classical sliding window object detection paradigm. We observe that generic objects with well-defined closed boundary can be dis
State-of-the-art object detection networks depend on region proposal algorithms to hypothesize object locations. Advances like SPPnet [7] and Fast R-CNN [5] have reduced the running time of these detection networks, exposing region proposal computat
this demo shows how to use Saliency Objectness[1], as well as Saliency
Optimization[2], Saliency Filter[3], Geodesic Saliency[4],
and Manifold Ranking[5].
Code for [1] by Sai Srivatsa R
Email : saisrivatsan12gmail.com
Date : 12/09/2015
Code for [
