Salient object detection (SOD) aims to mimic the human visual system (HVS) and cognition
mechanisms to identify and segment salient objects. However, due to the complexity of …

Can you find me? By simulating how humans to discover the so-called'perfectly'-
camouflaged object, we present a novel boundary-guided separated attention network (call …

The High-Resolution Transformer (HRFormer) can maintain high-resolution representation
and share global receptive fields. It is friendly towards salient object detection (SOD) in …

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

Camouflaged object detection is a challenging task that aims to identify objects having
similar texture to the surroundings. This paper presents to amplify the subtle texture …

Salient object detection (SOD) in optical remote sense images (ORSIs) is a valuable and
challenging task. The factors in ORSI, such as background clutter, lighting shadows, imaging …

Compared with RGB salient object detection (SOD) methods, RGB-D SOD models show
better performance in many challenging scenarios by leveraging spatial information …

Contexts play an important role in salient object detection (SOD). High-level contexts
describe the relations between different parts/objects and thus are helpful for discovering the …

Due to the rapid development of deep learning, the performance of salient object detection
has been constantly refreshed. Nevertheless, it is still challenging for existing methods to …

In this paper, we identify and address a serious design bias of existing salient object
detection (SOD) datasets, which unrealistically assume that each image should contain at …