Recently, relying on convolutional neural networks (CNNs), many methods for salient object
detection in optical remote-sensing images (ORSI-SOD) are proposed. However, most …

RGB-D Salient Object Detection (RGB-D SOD) aims at detecting remarkable objects by
complementary information from RGB images and depth cues. Although many outstanding …

Salient object detection (SOD) of images refers to simulating the attention mechanism of
human vision to capture the most attractive objects in an image. Current SOD mainly relies …

Existing methods for Salient Object Detection in Optical Remote Sensing Images (ORSI-
SOD) mainly adopt Convolutional Neural Networks (CNNs) as the backbone, such as VGG …

The 3-D object detection with light detection and ranging (LiDAR) point clouds is a
challenging problem, which requires 3-D scene understanding, yet this task is critical to …

Current state-of-the-art remote sensing salient object detectors always require high-
resolution spatial context to ensure excellent performance, which incurs enormous …

Salient object detection (SOD) in optical remote sensing images (RSIs) plays a significant
role in many areas such as agriculture, environmental protection, and the military. However …

Existing remote sensing image salient object detection (RSI-SOD) methods widely perform
object-level semantic understanding with pixel-level supervision, but ignore the image-level …

Motivated by the pursuit of efficient salient object detection in remote sensing, researchers
have devoted considerable efforts to devising lightweight models due to low running …

Abstract Recently, red-green-blue (RGB) and thermal (RGB-T) data have attracted
considerable interest for semantic segmentation because they provide robust imaging under …