In this paper, we propose a multi-center convex hull prior based solution for saliency detection. Particularly, our solution also integrates two non-trivial ...

ABSTRACT. Saliency detection has been a hot topic in computer vision. Among existing approaches, a representative one is to use the convex hull prior to ...

In this paper, we propose a multi-center convex hull prior based solution for salient object detection. ... using multiple centers (say k), where k is an integer.

KinD [25] developed three subnetworks for layer decomposition, reflectance restoration, and illumination adjustment, separately. Fan et al.

In this paper, we propose a multi-center convex hull prior based solution for saliency detection. Particularly, our solution also integrates two non-trivial ...

Hu et al. [47] used the central bias and the reweighting of the salient regions in the convex hull to guide the prior map. Compared with ...

Salient object detection has received much attention in the past decades. One of the representative approaches is utilizing the convex hull prior to find ...

In this paper, we propose a multi-center convex hull prior based solution for salient object detection. To strengthen our solution, we also integrate two non- ...

A novel bottom-up salient object detection approach by exploiting contrast, center and smoothness priors is presented and the smoothness prior enables the ...

We propose a new saliency detection algorithm via multi-level feature learning that takes advantage of deep neural networks' capacity to compute saliency values ...