A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A framework for multiple-instance learning
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Object Recognition as Machine Translation: Learning a Lexicon for a Fixed Image Vocabulary
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Contrast-based image attention analysis by using fuzzy growing
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Image Categorization by Learning and Reasoning with Regions
The Journal of Machine Learning Research
Region based image annotation through multiple-instance learning
Proceedings of the 13th annual ACM international conference on Multimedia
MISSL: multiple-instance semi-supervised learning
ICML '06 Proceedings of the 23rd international conference on Machine learning
MILES: Multiple-Instance Learning via Embedded Instance Selection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Incorporating multiple SVMs for automatic image annotation
Pattern Recognition
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Typicality ranking via semi-supervised multiple-instance learning
Proceedings of the 15th international conference on Multimedia
Image retrieval: Ideas, influences, and trends of the new age
ACM Computing Surveys (CSUR)
Annotating Images by Mining Image Search Results
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 18th international conference on World wide web
Image tag clarity: in search of visual-representative tags for social images
WSM '09 Proceedings of the first SIGMM workshop on Social media
Using large-scale web data to facilitate textual query based retrieval of consumer photos
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Label to region by bi-layer sparsity priors
MM '09 Proceedings of the 17th ACM international conference on Multimedia
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Boost search relevance for tag-based social image retrieval
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Learning social tag relevance by neighbor voting
IEEE Transactions on Multimedia
Multiple Bernoulli relevance models for image and video annotation
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Learning to Detect a Salient Object
IEEE Transactions on Pattern Analysis and Machine Intelligence
Content-based tag processing for Internet social images
Multimedia Tools and Applications
Assistive tagging: A survey of multimedia tagging with human-computer joint exploration
ACM Computing Surveys (CSUR)
Tag ranking by propagating relevance over tag and image graphs
Proceedings of the 4th International Conference on Internet Multimedia Computing and Service
Towards relevance and saliency ranking of image tags
Proceedings of the 20th ACM international conference on Multimedia
Personalized image recommendation and retrieval via latent SVM based model
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Adaptive all-season image tag ranking by saliency-driven image pre-classification
Journal of Visual Communication and Image Representation
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Tag ranking has emerged as an important research topic recently due to its potential application on web image search. Conventional tag ranking approaches mainly rank the tags according to their relevance levels with respect to a given image. Nonetheless, such algorithms heavily rely on the large-scale image dataset and the proper similarity measurement to retrieve semantic relevant images with multi-labels. In contrast to the existing tag relevance ranking algorithms, in this paper, we propose a novel tag saliency ranking scheme, which aims to automatically rank the tags associated with a given image according to their saliency to the image content. To this end, this paper presents an integrated framework for tag saliency ranking which combines both visual attention model and multi-instance learning algorithm to investigate the saliency ranking order information of tags with respect to the given image. Specifically, tags annotated on the image-level are propagated to the region-level via an efficient multi-instance learning algorithm firstly; then, visual attention model is employed to measure the importance of regions in the given image. And finally, tags are ranked according to the saliency values of the corresponding regions. Experiments conducted on the COREL and MSRC image datasets demonstrate the effectiveness and efficiency of the proposed framework.