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 …

Feature detection is a fundamental and important problem in computer vision and image
processing. It is a low-level processing step which serves as the essential part for computer …

Salient object detection has recently witnessed substantial progress due to powerful
features extracted using deep convolutional neural networks (CNNs). However, existing …

Visual saliency is a fundamental problem in both cognitive and computational sciences,
including computer vision. In this paper, we discover that a high-quality visual saliency …

Recent progresses in salient object detection have exploited the boundary prior, or
background information, to assist other saliency cues such as contrast, achieving state-of …

As an interesting and emerging topic, co-saliency detection aims at simultaneously
extracting common salient objects from a group of images. On one hand, traditional co …

Visual saliency is a fundamental problem in both cognitive and computational sciences,
including computer vision. In this paper, we discover that a high-quality visual saliency …

We extensively compare, qualitatively and quantitatively, 41 state-of-the-art models (29
salient object detection, 10 fixation prediction, 1 objectness, and 1 baseline) over seven …

Existing saliency detection approaches use images as inputs and are sensitive to
foreground/background similarities, complex background textures, and occlusions. We …

Low-rank recovery models have shown potential for salient object detection, where a matrix
is decomposed into a low-rank matrix representing image background and a sparse matrix …