Semantic context learning with large-scale weakly-labeled image set

ACM International Conference Proceeding Series

Volumn , Issue , 2012, Pages 1859-1863

  Lu, Yao ^a   Zhang, Wei ^a   Zhang, Ke ^a   Xue, Xiangyang ^a  

^a FUDAN UNIVERSITY   (China)

Author keywords

image annotation; large scale; semantic context; weakly labeled

Indexed keywords

DATA CLOUDS; IMAGE ANNOTATION; IMAGE SETS; INTERNET USERS; LARGE SCALE; MANUAL ANNOTATION; MULTI-LABEL ANNOTATION; MULTIPLE LABELS; REAL APPLICATIONS; REAL-WORLD IMAGE; SCALABILITY ISSUE; SEMANTIC CONTEXT; SEMANTIC SPACE; SEMI-SUPERVISED; TAGGING SYSTEMS; VISUAL CONTEXT; WEAKLY LABELED; WEB IMAGES;

ITERATIVE METHODS; KNOWLEDGE MANAGEMENT; SEMANTICS;

SEMANTIC WEB;

EID: 84871091658     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2396761.2398532     Document Type: Conference Paper

References (23)

1. M. Belkin, P. Niyogi, and V. Sindhwani. Manifold regularization: A geometric framework for learning from labeled and unlabeled examples. JMLR, 7:2399-2434, 2006.
2. L. Chen, D. Xu, I. W. Tsang, and J. Luo. Tag-based web photo retrieval improved by batch mode re-tagging. In CVPR, 2010.
3. X. Chen, Y. Mu, S. Yan, and T.-S. Chua. Efficient large-scale image annotation by probabilistic collaborative multi-label propagation. In ACM MM, 2010.
4. M. J. Choi, J. J. Lim, A. Torralba, and A. S. Willsky. Exploiting hierarchical context on a large database of object categories. In CVPR, 2010.
5. T.-S. Chua, J. Tang, R. Hong, H. Li, Z. Luo, and Y.-T. Zheng. Nus-wide: A real-world web image database from national university of singapore. In CIVR, 2009.
6. J. Fan, Y. Shen, N. Zhou, and Y. Gao. Harvesting large-scale weakly-tagged image databases from the web. In CVPR, 2010.
7. S. L. Feng, R. Manmatha, and V. Lavrenko. Multiple bernoulli relevance models for image and video annotation. In CVPR, 2004.
8. R. Fergus, Y. Weiss, and A. Torralba. Semi-supervised learning in gigantic image collections. In NIPS, 2010.
9. M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. In ICCV, 2009.
10. D. Liu, X.-S. Hua, M. Wang, and H.-J. Zhang. Image retagging. In ACM MM, 2010.
11. D. Liu, S. Yan, Y. Rui, and H.-J. Zhang. Unified tag analysis with multi-edge graph. In ACM MM, 2010.
12. W. Liu, J. He, and S.-F. Chang. Large graph construction for scalable semi-supervised learning. In ICML, 2010.
13. A. Makadia, V. Pavlovic, and S. Kumar. A new baseline for image annotation. In ECCV, 2008.
14. S. T. Roweis and L. K. Saul. Nonlinear dimensionality reduction by locally linear embedding. Science, vol. 290, 2000.
15. X. Rui, M. Li, Z. Li, W.-Y. Ma, and N. Yu. Bipartite graph reinforcement model for web image annotation. In ACM MM, 2007.
16. J. Tang, S. Yan, R. Hong, G.-J. Qi, and T.-S. Chua. Inferring semantic concepts from community contributed images and noisy tags. In ACM MM, 2009.
17. C. Wang, F. Jing, L. Zhang, and H.-J. Zhang. Content-based image annotation refinement. In CVPR, 2007.
18. L. Wu, X.-S. Hua, N. Yu, W.-Y. Ma, and S. Li. Flickr distance. In ACM MM, 2008.
19. Z.-J. Zha, X.-S. Hua, T. Mei, J. Wang, G.-J. Qi, and Z. Wang. Joint multi-label multi-instance learning for image classification. In CVPR, 2008.
20. Z.-J. Zha, T. Mei, J. Wang, Z. Wang, and X.-S. Hua. Graph-based semi-supervised learning with multiple labels. J. Vis. Commun. Image R., 2009.
21. W. Zhang, Y. Lu, X. Xue, and J. Fan. Automatic image annotation with weakly labeled dataset. In ACM MM, 2011.
22. G. Zhu, S. Yan, and Y. Ma. Image tag refinement towards low-rank, content-tag prior and error sparsity. In ACM MM, 2010.
23. X. Zhu, Z. Ghahramani, and J. Lafferty. Semi-supervised learning using gaussian fields and harmonic functions. In ICML, 2003.