Most recent methods for RGB (red–green–blue)-thermal salient object detection (SOD)
involve several floating-point operations and have numerous parameters, resulting in slow …

Recently, fully convolutional networks (FCNs) have made great progress in the task of
salient object detection and existing state-of-the-arts methods mainly focus on how to …

The infrared small and dim (S&D) target detection is one of the key techniques in the infrared
search and tracking system. Since the local regions similar to infrared S&D targets spread …

The application of optical remote sensing images (ORSIs) is prevalent in many fields.
Accordingly, ORSI-oriented salient object detection (SOD) has attracted more attention in …

Camouflaged object segmentation (COS) is a very challenging task due to the deceitful
appearances of the candidate objects to the noisy backgrounds. Most existing state-of-the …

In this paper, we identify and address a serious design bias of existing salient object
detection (SOD) datasets, which unrealistically assume that each image should contain at …

Salient object detection (SOD) is an important task in computer vision that aims to identify
visually conspicuous regions in images. RGB-Thermal SOD combines two spectra to …

Point clouds produced by laser scanners are an invaluable source of data for reconstructing
multi-dimensional digital models that reflect the as-is conditions of built facilities. However …

Human-Object Interaction (HOI) Detection is an important task to understand how humans
interact with objects. Most of the existing works treat this task as an exhaustive triplet< …

Finding tampered regions in images is a common research topic in machine learning and
computer vision. Although many image manipulation location algorithms have been …