Co-saliency detection is a newly emerging and rapidly growing research area in the
computer vision community. As a novel branch of visual saliency, co-saliency detection …

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 …

This paper proposes a deep learning model to efficiently detect salient regions in videos. It
addresses two important issues: 1) deep video saliency model training with the absence of …

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 …

Predicting where people look in static scenes, aka visual saliency, has received significant
research interest recently. However, relatively less effort has been spent in understanding …

This paper conducts a systematic study on the role of visual attention in Unsupervised Video
Object Segmentation (UVOS) tasks. By elaborately annotating three popular video …

The human attention mechanism can be understood and simulated by closely associating
the saliency prediction task to neuroscience and psychology. Furthermore, saliency …

This paper proposes a fast video salient object detection model, based on a novel recurrent
network architecture, named Pyramid Dilated Bidirectional ConvLSTM (PDB-ConvLSTM). A …

We present a survey on maritime object detection and tracking approaches, which are
essential for the development of a navigational system for autonomous ships. The electro …

In this work, we contribute to video saliency research in two ways. First, we introduce a new
benchmark for predicting human eye movements during dynamic scene free-viewing, which …