Detection and localization of regions of images that attract immediate human visual attention
is currently an intensive area of research in computer vision. The capability of automatic …

Contexts play an important role in the saliency detection task. However, given a context
region, not all contextual information is helpful for the final task. In this paper, we propose a …

Skin Cancer accounts for one-third of all diagnosed cancers worldwide. The prevalence of
skin cancers have been rising over the past decades. In recent years, use of dermoscopy …

In this paper, we aim to predict human eye fixation with view-free scenes based on an end-to-
end deep learning architecture. Although convolutional neural networks (CNNs) have made …

Salient object detection (SOD) in optical remote sensing images (RSIs) is a valuable and
challenging task. Although many SOD methods for RSIs have been proposed, there are still …

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 …

Recent progress on salient object detection (SOD) mainly benefits from multi-scale learning,
where the high-level and low-level features collaborate in locating salient objects and …

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 …

In this paper, we aim to develop an efficient and compact deep network for RGB-D salient
object detection, where the depth image provides complementary information to boost …

The eight-volume set comprising LNCS volumes 9905-9912 constitutes the refereed
proceedings of the 14th European Conference on Computer Vision, ECCV 2016, held in …