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 …

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 …

The visual saliency detection model simulates the human visual system to perceive the
scene and has been widely used in many vision tasks. With the development of acquisition …

Salient object detection from RGB-D images is an important yet challenging vision task,
which aims at detecting the most distinctive objects in a scene by combining color …

The goal of co-salient object detection (CoSOD) is to discover salient objects that commonly
appear in a query group containing two or more relevant images. Therefore, how to …

In this article, we conduct a comprehensive study on the co-salient object detection (CoSOD)
problem for images. CoSOD is an emerging and rapidly growing extension of salient object …

We present a novel group collaborative learning framework (GCNet) capable of detecting co-
salient objects in real time (16ms), by simultaneously mining consensus representations at …

Most previous co-salient object detection works mainly focus on extracting co-salient cues
via mining the consistency relations across images while ignoring the explicit exploration of …

The detection results of many existing co-saliency detection methods are easily interfered by
the unrelated salient objects, which have similar appearance characteristics to co-salient …

Co-saliency detection (Co-SOD) aims to segment the common salient foreground in a group
of relevant images. In this paper, inspired by human behavior, we propose a gradient …