In this paper, we aim to develop an efficient and compact deep network for RGB-D salient
object detection, where the depth image provides complementary information to boost …

Recent years have witnessed a big leap in automatic visual saliency detection attributed to
advances in deep learning, especially Convolutional Neural Networks (CNNs). However …

Due to the rapid development of artificial intelligence technology, industrial sectors are
revolutionizing in automation, reliability, and robustness, thereby significantly increasing …

RGB-D salient object detection (SOD) aims to segment the most attractive objects in a pair of
cross-modal RGB and depth images. Currently, most existing RGB-D SOD methods focus on …

RGB-induced salient object detection has recently witnessed substantial progress, which is
attributed to the superior feature learning capability of deep convolutional neural networks …

Salient object detection identifies objects in an image that grab visual attention. Although
contextual features are considered in recent literature, they often fail in real-world complex …

Convolutional neural networks (CNNs) have significantly advanced computational
modelling for saliency prediction. However, accurately simulating the mechanisms of visual …

Recently, the Part-Object Relational (POR) saliency underpinned by the Capsule Network
(CapsNet) has been demonstrated to be an effective modeling mechanism to improve the …

Abstract Visual Feature Learning (VFL) is a critical area of research in computer vision that
involves the automatic extraction of features and patterns from images and videos. The …

Abstract Despite Convolutional Neural Networks (CNNs) based methods have been
successful in detecting salient objects, their underlying mechanism that decides the salient …