Saliency detection is useful for many computer vision tasks including content-based image retrieval, segmentation, and object detection. However, methods on saliency detection are usually greatly affected by factors like features and segmentation results. We propose a novel selective segmentation-based saliency detection model to decrease the side effects caused by these factors. After extracti...

This paper proposes a novel saliency detection method by combining region-level saliency estimation and pixel-level saliency prediction with CNNs (denoted as CRPSD). For pixel-level saliency prediction, a fully convolutional neural network (called pixel-level CNN) is constructed by modifying the VGGNet architecture to perform multiscale feature learning, based on which an image-to-image predict...

Salient region detection in images is very useful for image processing applications like image compressing, image segmentation, object detection and recognition. In this paper, an improved approach to detect salient region is presented. The proposed method can generate a robust saliency map and extract salient regions with precise boundaries. In the proposed method, local saliency, global salie...

Because saliency can be used as the prior knowledge of image content, saliency detection has been an active research area in image segmentation, object detection, image semantic understanding and other relevant image-based applications. In the case of saliency detection from cluster scenes, the salient object/region detected needs to not only be distinguished clearly from the background, but, p...

The success of current deep saliency detection methods heavily depends on the availability of large-scale supervision in the form of per-pixel labeling. Such supervision, while labor-intensive and not always possible, tends to hinder the generalization ability of the learned models. By contrast, traditional handcrafted features based unsupervised saliency detection methods, even though have bee...

A low-complexity saliency detection algorithm for perceptual video coding is proposed; low-level encoding information is adopted as the characteristics of visual perception analysis. Firstly, this algorithm employs motion vector (MV) to extract temporal saliency region through fast MV noise filtering and translational MV checking procedure. Secondly, spatial saliency region is detected based on...

We present a new segment-based method for saliency detection based on multi-size superpixels that combines local and global saliency cues. We extract superpixels at several scales and represent each superpixel with a normal distribution in CIE-Lab space estimated from its associated pixels. Global saliency is computed by grouping similar superpixels to estimate the spatial distribution of color...

We discuss two experiments that deal with saliency in videos. In the first experiment, we combine motion detection algorithms with a context-aware saliency detection algorithm to add motion as a feature in video saliency. In the second experiment, we apply principles from spatial saliency in static images to pick out salient frames in a video.

Saliency detection is an active topic in multimedia field. Several algorithms have been proposed in this field. Most previous works on saliency detection focus on 2D images. However, for some complex situations which contain multiple objects or complex background, they are not robust and their performances are not satisfied. Recently, 3D visual information supplies a powerful cue for saliency d...

Human visual system actively seeks salient regions and movements in video sequences to reduce the search effort. Computational visual saliency detection model provides important information for semantic understanding in many real world applications. In this paper, we propose a novel perception-oriented video saliency detection model to detect the attended regions for both interesting objects an...