Title
Saliency Aggregation: Multifeature and Neighbor Based Salient Region Detection for Social Images
Abstract
AbstractThe popularity of social networks has brought the rapid growth of social images which have become an increasingly important image type. One of the most obvious attributes of social images is the tag. However, the sate-of-the-art methods fail to fully exploit the tag information for saliency detection. Thus this paper focuses on salient region detection of social images using both image appearance features and image tag cues. First, a deep convolution neural network is built, which considers both appearance features and tag features. Second, tag neighbor and appearance neighbor based saliency aggregation terms are added to the saliency model to enhance salient regions. The aggregation method is dependent on individual images and considers the performance gaps appropriately. Finally, we also have constructed a new large dataset of challenging social images and pixel-wise saliency annotations to promote further researches and evaluations of visual saliency models. Extensive experiments show that the proposed method performs well on not only the new dataset but also several state-of-the-art saliency datasets.
Year
DOI
Venue
2018
10.1155/2018/1014595
Periodicals
Field
DocType
Volume
Social network,Pattern recognition,Computer science,Convolutional neural network,Salience (neuroscience),Popularity,Exploit,Artificial intelligence,Region detection,Machine learning,Salient,Visual saliency
Journal
2018
Issue
ISSN
Citations 
1
1687-9724
1
PageRank 
References 
Authors
0.35
12
5
Name
Order
Citations
PageRank
Ye Liang165.39
Congyan Lang235339.20
Jian Yu31347149.17
Hongzhe Liu45610.93
Nan Ma597.93