Salient object detection, which simulates human visual perception in locating the most
significant object (s) in a scene, has been widely applied to various computer vision tasks …

Convolutional neural network (CNN)-based encoder-decoder models have profoundly
inspired recent works in the field of salient object detection (SOD). With the rapid …

In this paper, we design a simple yet powerful deep network architecture, U 2-Net, for salient
object detection (SOD). The architecture of our U 2-Net is a two-level nested U-structure. The …

Deep-learning based salient object detection methods achieve great progress. However, the
variable scale and unknown category of salient objects are great challenges all the time …

Fully convolutional neural networks (FCNs) have shown their advantages in the salient
object detection task. However, most existing FCNs-based methods still suffer from coarse …

Abstract Deep Convolutional Neural Networks have been adopted for salient object
detection and achieved the state-of-the-art performance. Most of the previous works …

We solve the problem of salient object detection by investigating how to expand the role of
pooling in convolutional neural networks. Based on the U-shape architecture, we first build a …

Recently, contour information largely improves the performance of saliency detection.
However, the discussion on the correlation between saliency and contour remains scarce. In …

Saliency detection is one of the basic challenges in computer vision. Recently, CNNs are the
most widely used and powerful techniques for saliency detection, in which feature maps …

As an essential problem in computer vision, salient object detection (SOD) has attracted an
increasing amount of research attention over the years. Recent advances in SOD are …