Salient object detection (SOD) and camouflaged object detection (COD) are related yet
distinct binary map** tasks. These tasks involve multiple modalities sharing …

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 …

The ability to capture inter-frame dynamics has been critical to the development of video
salient object detection (VSOD). While many works have achieved great success in this field …

Research on the detection of objects at crime scenes has flourished in the last two decades.
Researchers have been concentrating on color pictures, where lighting is a crucial …

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

Unsupervised video object segmentation (UVOS) aims at segmenting the primary objects in
videos without any human intervention. Due to the lack of prior knowledge about the primary …

Significant performance improvement has been achieved for fully-supervised video salient
object detection with the pixel-wise labeled training datasets, which are timeconsuming and …

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 the field of diagnosis and treatment planning of Coronavirus disease 2019 (COVID-19),
accurate infected area segmentation is challenging due to the significant variations in the …

We have witnessed a growing interest in video salient object detection (VSOD) techniques
in today's computer vision applications. In contrast with temporal information (which is still …