In recent years, the Convolutional Neural Network (CNN) has been widely used in various
visual tasks because of its powerful feature extraction ability. Salient object detection …

In this paper, we propose an efficient and discriminative saliency method that takes
advantage of background divergence and foreground compactness. Concretely, a graph is …

There have been remarkable improvements in the salient object detection in the recent
years. During the past few years, graph-based saliency detection algorithms have been …

Given that existing salient object detection methods cannot effectively predict the fine
contours of salient objects when extracting local or global contexts and features, we propose …

Salient object detection is a challenging task, and several methods have been proposed for
the same in the literature. The problem lies in that most of the methods perform good on a …

Salient object detection represents a novel preprocessing stage of many practical image
applications in the discipline of computer vision. Saliency detection is generally a complex …

The Hierarchical Max-pooling models (HMAX) have demonstrated excellent outperformance
when integrated with various computer vision algorithms for the purpose of recognizing …

Recent deep learning-based methods for saliency detection have proved the effectiveness
of integrating features with different scales. They usually design various complex …

Salient Object Detection (SOD) can mimic the human vision system by using algorithms that
simulate the way how the eye detects and processes visual information. It focuses mainly on …

In this paper, we present a novel method to detect salient object based on multi-level cues.
First, a proposal processing scheme is developed by various object-level saliency cues to …