Abstract RGB-Thermal infrared (RGB-T) image analysis has been actively studied in recent
years. In the past decade, it has received wide attention and made a lot of important …

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

This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …

This research focuses on the discovery and localization of hidden objects in the wild and
serves unmanned systems. Through empirical analysis, infrared and visible image fusion …

In recent years, RGB-T salient object detection (SOD) has attracted continuous attention,
which makes it possible to identify salient objects in environments such as low light by …

Significant advances have been achieved in object detection techniques using visible
images for applications that include military operations, autonomous driving, and security …

The High-Resolution Transformer (HRFormer) can maintain high-resolution representation
and share global receptive fields. It is friendly towards salient object detection (SOD) in …

The ability of capturing the complementary information of multi-modality data is critical to the
development of multi-modality salient object detection (SOD). Most of existing studies …

RGB-based salient object detection (SOD) algorithms have shown good ability to segment
salient objects from images, but the performance is still unsatisfactory when dealing with …

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 …