Detection and localization of regions of images that attract immediate human visual attention
is currently an intensive area of research in computer vision. The capability of automatic …

Salient object detection (SOD) is a long-standing research topic in computer vision with
increasing interest in the past decade. Since light fields record comprehensive information of …

Feature fusion, the combination of features from different layers or branches, is an
omnipresent part of modern network architectures. It is often implemented via simple …

Existing RGB-D salient object detection (SOD) models usually treat RGB and depth as
independent information and design separate networks for feature extraction from each …

Abstract Camouflaged Object Detection (COD) aims to detect objects with similar patterns
(eg, texture, intensity, colour, etc) to their surroundings, and recently has attracted growing …

Skin Cancer accounts for one-third of all diagnosed cancers worldwide. The prevalence of
skin cancers have been rising over the past decades. In recent years, use of dermoscopy …

The advent of large vision-language models (LVLMs) represents a remarkable advance in
the quest for artificial general intelligence. However, the models' effectiveness in both …

Automatic change detection from remotely sensed imagery is extremely important for many
applications, including land use mapping. In recent years, a growing number of researchers …

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 …

Image segmentation plays an important role in the computer vision. However, it is extremely
challenging due to low resolution, high noise and blurry boundaries. Recently, region-based …