In recent years, salient object detection (SOD) has achieved significant progress with the
help of convolution neural network (CNN). Most of the state-of-the-art methods segment the …

How to effectively utilize and fuse deep features has become a critical point for salient object
detection. Most existing methods usually adopt the convolutional features based on U-shape …

Salient object detection aims at locating the most conspicuous objects in natural images,
which usually acts as a very important pre-processing procedure in many computer vision …

Salient Object Detection aims to detect the most visually distinctive objects in an image. We
solve this problem by introducing the average pool to explore the multi-level deep average …

Feature pyramid network (FPN) based models, which fuse the semantics and salient details
in a progressive manner, have been proven highly effective in salient object detection …

Deep convolutional neural networks have achieved competitive performance in salient
object detection, in which how to learn effective and comprehensive features plays a critical …

Convolutional Neural Network (CNN) has shown their advantages in salient object
detection. CNN can generate great saliency maps because it can obtain high-level semantic …

High-level semantic features and low-level detail features matter for salient object detection
in fully convolutional neural networks (FCNs). Further integration of low-level and high-level …

The multi-scale features and the fusion strategy of contextual features are the keys to salient
object detection task. Previous multi-scale-based works often overlooked the completeness …

Recently, fully convolutional neural networks have been adopted for salient object detection
and object contour detection, and have achieved impressive performance. Closely related …