Convolutional neural network (CNN)-based encoder-decoder models have profoundly
inspired recent works in the field of salient object detection (SOD). With the rapid …

Sight and hearing are two senses that play a vital role in human communication and scene
understanding. To mimic human perception ability, audio-visual learning, aimed at …

Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …

Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …

The last decade has witnessed a growing interest in video salient object detection (VSOD).
However, the research community long-term lacked a well-established VSOD dataset …

The visual saliency detection model simulates the human visual system to perceive the
scene and has been widely used in many vision tasks. With the development of acquisition …

Salient object detection from RGB-D images is an important yet challenging vision task,
which aims at detecting the most distinctive objects in a scene by combining color …

Video salient object detection aims at discovering the most visually distinctive objects in a
video. How to effectively take object motion into consideration during video salient object …

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 …

Image saliency detection has recently witnessed significant progress due to deep
convolutional neural networks. However, extending state-of-the-art saliency detectors from …