Graph classification is a fundamental problem with diverse applications in bioinformatics
and chemistry. Due to the intricate procedures of manual annotations in graphical domains …

RGB-D saliency detection is receiving more and more attention in recent years. There are
many efforts have been devoted to this area, where most of them try to integrate the multi …

Abstract Deep Learning-based Unsupervised Salient Object Detection (USOD) mainly relies
on the noisy saliency pseudo labels that have been generated from traditional handcraft …

In this work, we propose a novel depth-induced multi-scale recurrent attention network for
RGB-D saliency detection, named as DMRA. It achieves dramatic performance especially in …

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 …

In this paper, we present a weakly-supervised RGB-D salient object detection model via
scribble supervision. Specifically, as a multimodal learning task, we focus on effective …

Most of the existing deep learning based salient object detection (SOD) models adopt multi-
level feature fusion strategies, and have achieved remarkable progress. However, current …