Traditional1 salient object detection models often use hand-crafted features to formulate
contrast and various prior knowledge, and then combine them artificially. In this work, we …

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

Deep networks have been proved to encode high level semantic features and delivered
superior performance in saliency detection. In this paper, we go one step further by …

Recent advances in saliency detection have utilized deep learning to obtain high level
features to detect salient regions in a scene. They have demonstrated superior results over …

A key problem in salient object detection is how to effectively model the semantic properties
of salient objects in a data-driven manner. In this paper, we propose a multi-task deep …

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 …

In this paper, we present a real-time salient object detection system based on the minimum
spanning tree. Due to the fact that background regions are typically connected to the image …

Top-down visual saliency is an important module of visual attention. In this work, we propose
a novel top-down saliency model that jointly learns a Conditional Random Field (CRF) and a …

Human eye fixations often correlate with locations of salient objects in the scene. However,
only a handful of approaches have attempted to simultaneously address the related aspects …

Parsing articulated objects, eg. humans and animals, into semantic parts (eg. head, body
and arms, etc.) from natural images is a challenging and fundamental problem in computer …