Concealed scene understanding (CSU) is a hot computer vision topic aiming to perceive
objects exhibiting camouflage. The current boom in terms of techniques and applications …

This paper presents a comprehensive survey on vision-based robotic gras**. We
conclude three key tasks during vision-based robotic gras**, which are object localization …

Existing state-of-the-art saliency detection methods heavily rely on CNN-based
architectures. Alternatively, we rethink this task from a convolution-free sequence-to …

Capsule networks (CapsNets) have been known difficult to develop a deeper architecture,
which is desirable for high performance in the deep learning era, due to the complex …

Although current salient object detection (SOD) works have achieved significant progress,
they are limited when it comes to the integrity of the predicted salient regions. We define the …

As an essential problem in computer vision, salient object detection (SOD) has attracted an
increasing amount of research attention over the years. Recent advances in SOD are …

In this paper, we propose the first framework (UCNet) to employ uncertainty for RGB-D
saliency detection by learning from the data labeling process. Existing RGB-D saliency …

Abstract Deep Supervised Salient Object Detection (SSOD) excessively relies on large-
scale annotated pixel-level labels which consume intensive labour acquiring high quality …

Contrast and part-whole relations induced by deep neural networks like Convolutional
Neural Networks (CNNs) and Capsule Networks (CapsNets) have been known as two types …

Salient Object Detection has boomed in recent years and achieved impressive performance
on regular-scale targets. However, existing methods encounter performance bottlenecks in …