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

This paper presents a comprehensive survey on vision-based robotic grasping. We
conclude three key tasks during vision-based robotic grasping, which are object localization …

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 …

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 …

This paper presents a new method for detecting salient objects in images using
convolutional neural networks (CNNs). The proposed network, named PAGE-Net, offers two …

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 …

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 …

Contexts play an important role in the saliency detection task. However, given a context
region, not all contextual information is helpful for the final task. In this paper, we propose a …

Saliency detection aims to highlight the most relevant objects in an image. Methods using
conventional models struggle whenever salient objects are pictured on top of a cluttered …

This paper proposes a deep learning model to efficiently detect salient regions in videos. It
addresses two important issues: 1) deep video saliency model training with the absence of …