Appearance and motion are two important sources of information in video object
segmentation (VOS). Previous methods mainly focus on using simplex solutions, lowering …

Video saliency detection (VSD) aims at fast locating the most attractive
objects/things/patterns in a given video clip. Existing VSD-related works have mainly relied …

Fully-supervised salient object detection (SOD) methods have made great progress, but
such methods often rely on a large number of pixel-level annotations, which are time …

Fully supervised video salient object detection models have achieved excellent
performance, yet obtaining pixel-by-pixel annotated datasets is laborious. Several works …

RGB-depth (RGB-D) salient object detection (SOD) recently has attracted increasing
research interest, and many deep learning methods based on encoder–decoder …

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

This paper proposes a scribble-based weakly supervised RGB-D salient object detection
(SOD) method to relieve the annotation burden from pixel-wise annotations. In view of the …

For the video salient object detection (VSOD) task, how to excavate the information from the
appearance modality and the motion modality has always been a topic of great concern. The …

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 …

Video salient object detection is a fundamental computer vision task aimed at highlighting
the most conspicuous objects in a video sequence. There are two key challenges presented …