Efficient and effective querying by image content
Journal of Intelligent Information Systems - Special issue: advances in visual information management systems
Photobook: content-based manipulation of image databases
International Journal of Computer Vision
VisualSEEk: a fully automated content-based image query system
MULTIMEDIA '96 Proceedings of the fourth ACM international conference on Multimedia
Algorithm 582: The Gibbs-Poole-Stockmeyer and Gibbs-King Algorithms for Reordering Sparse Matrices
ACM Transactions on Mathematical Software (TOMS)
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
Optimizing search engines using clickthrough data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic image annotation and retrieval using cross-media relevance models
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
An efficient boosting algorithm for combining preferences
The Journal of Machine Learning Research
Automatic multimedia cross-modal correlation discovery
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Effective automatic image annotation via a coherent language model and active learning
Proceedings of the 12th annual ACM international conference on Multimedia
Image annotations by combining multiple evidence & wordNet
Proceedings of the 13th annual ACM international conference on Multimedia
Learning to rank using gradient descent
ICML '05 Proceedings of the 22nd international conference on Machine learning
Label propagation through linear neighborhoods
ICML '06 Proceedings of the 23rd international conference on Machine learning
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Correlated Label Propagation with Application to Multi-label Learning
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Image annotation refinement using random walk with restarts
MULTIMEDIA '06 Proceedings of the 14th annual ACM international conference on Multimedia
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Supervised Learning of Semantic Classes for Image Annotation and Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning to rank: from pairwise approach to listwise approach
Proceedings of the 24th international conference on Machine learning
A support vector method for optimizing average precision
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
AdaRank: a boosting algorithm for information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Dual cross-media relevance model for image annotation
Proceedings of the 15th international conference on Multimedia
Learning to reduce the semantic gap in web image retrieval and annotation
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image annotation via graph learning
Pattern Recognition
A New Baseline for Image Annotation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
Semi-supervised kernel density estimation for video annotation
Computer Vision and Image Understanding
Semi-supervised multi-label learning by constrained non-negative matrix factorization
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Inferring semantic concepts from community-contributed images and noisy tags
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Image annotation using clickthrough data
Proceedings of the ACM International Conference on Image and Video Retrieval
Context-based multi-label image annotation
Proceedings of the ACM International Conference on Image and Video Retrieval
NUS-WIDE: a real-world web image database from National University of Singapore
Proceedings of the ACM International Conference on Image and Video Retrieval
Image annotation and retrieval based on efficient learning of contextual latent space
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Efficient large-scale image annotation by probabilistic collaborative multi-label propagation
Proceedings of the international conference on Multimedia
Image annotation using multi-correlation probabilistic matrix factorization
Proceedings of the international conference 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 re-rank: query-dependent image re-ranking using click data
Proceedings of the 20th international conference on World wide web
Efficient multi-modal retrieval in conceptual space
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Image Annotation by Graph-Based Inference With Integrated Multiple/Single Instance Representations
IEEE Transactions on Multimedia
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
| Hi-index | 0.01 |
In this paper, we formulate image annotation as a Multi-correlation Learning to Rank (MLRank) problem, i.e., ranking the relevance of tags to an image considering the visual similarity and the semantic relevance. Unlike typical learning to rank algorithms, which assume that the ranking objects are independent, we attempt to rank relational data by exploring the consistency between ''visual similarity'' and ''semantic relevance''. The consistency means that similar images are usually annotated with relevant tags to reflect similar semantic themes, and vice versa. We define the two cases as the image-bias consistency and the tag-bias consistency respectively, which are both formulated into the optimization problem for rank learning. To obtain an explicit solution of the ranking model, we relax the optimization problem in two manners by attaching the constraints corresponding to the image-bias and tag-bias consistency with different sequential orders respectively, which lead to a uniform ranking model. Experimental results show that the proposed MLRank method outperforms the state-of-the-arts on three benchmarks including Corel5K, IAPR TC12 and NUS-WIDE.