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 …

Optical remote sensing images (RSIs) have been widely used in many applications, and one
of the interesting issues about optical RSIs is the salient object detection (SOD). However …

The last decade has witnessed a growing interest in video salient object detection (VSOD).
However, the research community long-term lacked a well-established VSOD dataset …

Salient object detection (SOD) in optical remote sensing images (RSIs) is a valuable and
challenging task. Although many SOD methods for RSIs have been proposed, there are still …

Predicting where people look in static scenes, aka visual saliency, has received significant
research interest recently. However, relatively less effort has been spent in understanding …

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 …

Data-driven saliency has recently gained a lot of attention thanks to the use of convolutional
neural networks for predicting gaze fixations. In this paper, we go beyond standard …

Paired RGB and depth images are becoming popular multi-modal data adopted in computer
vision tasks. Traditional methods based on Convolutional Neural Networks (CNNs) typically …

This paper conducts a systematic study on the role of visual attention in Unsupervised Video
Object Segmentation (UVOS) tasks. By elaborately annotating three popular video …

Recently, more and more researchers have paid attention to the surface defect detection of
strip steel. However, the performance of existing methods usually fails to detect the defect …