As a fundamental and important task in remote sensing, remote sensing image scene
understanding (RSISU) has attracted tremendous research interest in recent years. RSISU …

Co-saliency detection is a newly emerging and rapidly growing research area in the
computer vision community. As a novel branch of visual saliency, co-saliency detection …

Convolutional neural networks (CNNs) are good at extracting contexture features within
certain receptive fields, while transformers can model the global long-range dependency …

Remote sensing image scene classification is an active and challenging task driven by
many applications. More recently, with the advances of deep learning models especially …

The performance of object detection has recently been significantly improved due to the
powerful features learnt through convolutional neural networks (CNNs). Despite the …

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 …

RGB salient object detection (SOD) has made great progress. However, the performance of
this single-modal salient object detection will be significantly decreased when encountering …

As one of the fundamental research topics in remote sensing image analysis, hyperspectral
image (HSI) classification has been extensively studied so far. However, how to …

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 …

As humans we possess an intuitive ability for navigation which we master through years of
practice; however existing approaches to model this trait for diverse tasks including …