Image instance segmentation involves labeling pixels of images with classes and instances,
which is one of the pivotal technologies in many domains, such as natural scenes …

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 …

Most salient object detection approaches use U-Net or feature pyramid networks (FPN) as
their basic structures. These methods ignore two key problems when the encoder …

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 …

Although current salient object detection (SOD) works have achieved significant progress,
they are limited when it comes to the integrity of the predicted salient regions. We define the …

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 …

Existing state-of-the-art salient object detection networks rely on aggregating multi-level
features of pre-trained convolutional neural networks (CNNs). However, compared to high …

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 …

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

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 …