Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

We review the broad variety of methods that have been proposed for anomaly detection in
images. Most methods found in the literature have in mind a particular application. Yet we …

Robust driver attention prediction for critical situations is a challenging computer vision
problem, yet essential for autonomous driving. Because critical driving moments are so rare …

Data size is the bottleneck for developing deep saliency models, because collecting eye-
movement data is very time-consuming and expensive. Most of current studies on human …

Images captured in underwater environments usually exhibit complex illuminations, severe
turbidity of water, and often display objects with large varieties in pose and spatial location …

Saliency detection has been revealed an effective and reliable approach to extract the
region of interest (ROI) in remote sensing images. However, most existing saliency detection …

Blind image quality assessment (BIQA) is a fundamental yet challenging problem in the
image processing system. Existing BIQA models have the following problems: 1) Due to the …

High-resolution optical remote sensing data can be utilized to investigate the human
behavior and the activities of artificial targets, for example ship detection on the sea …

Accurate segmentation of apple fruit under natural illumination conditions provides benefits
for growers to plan relevant applications of nutrients and pesticides. It also plays an …

Saliency detection is a hot topic in recent years and much efforts have been made to
address it from different perspectives. However, current saliency models cannot meet the …