Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive
objects exhibiting camouflage. The current boom in terms of techniques and applications …

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 …

Benefit from the quick development of deep learning techniques, salient object detection has
achieved remarkable progresses recently. However, there still exists following two major …

We explore the potential of pooling techniques on the task of salient object detection by
expanding its role in convolutional neural networks. In general, two pooling-based modules …

Detection and localization of regions of images that attract immediate human visual attention
is currently an intensive area of research in computer vision. The capability of automatic …

We consider the problem of referring camouflaged object detection (Ref-COD), a new task
that aims to segment specified camouflaged objects based on a small set of referring images …

Salient object detection models mimic the behavior of human beings and capture the most
salient region/object from the images or scenes, this field contains many important …

Integration of multi-level contextual information, such as feature maps and side outputs, is
crucial for Convolutional Neural Networks (CNNs)-based salient object detection. However …

In this paper, we propose a bottom-up saliency model based on absorbing Markov chain
(AMC). First, a sparsely connected graph is constructed to capture the local context …