Decorrelating semantic visual attributes by resisting the urge to share

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 1629-1636

  Jayaraman, Dinesh ^a   Sha, Fei ^b   Grauman, Kristen ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b School of Pharmacy   (United States)

Author keywords

attribute conflation; attribute decorrelation; attribute groups; attribute learning; multitask learning; semantic attributes; structured sparsity; task groups; visual attributes

Indexed keywords

MULTI-TASK LEARNING; PATTERN RECOGNITION; SEMANTICS;

ATTRIBUTE CONFLATION; ATTRIBUTE GROUPS; ATTRIBUTE LEARNING; DE CORRELATIONS; SEMANTIC ATTRIBUTE; STRUCTURED SPARSITIES; TASK GROUPS; VISUAL ATTRIBUTES;

LEARNING SYSTEMS;

EID: 84911379042     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.211     Document Type: Conference Paper

References (33)

1. A. Argyriou, T. Evgeniou, and M. Pontil. Multi-Task Feature Learning. In NIPS, 2007.
2. F. Bach. Consistency of the group lasso and multiple kernel learning. In JMLR, 2008.
3. S. Branson, C. Wah, F. Schroff, B. Babenko, P. Welinder, P. Perona, and S. Belongie. Visual recognition with humans in the loop. In ECCV, 2010.
4. X. Chen, Q. Lin, S. Kim, J. G. Carbonell, and E. Xing. Smoothing proximal gradient method for general structured sparse regression. In AAS, 2012.
5. A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth. Describing Objects by Their Attributes. In CVPR, 2009.
6. P. Gardenfors. Conceptual spaces as a framework for knowledge representation. In Mind and Matter, 2004.
7. S. J. Hwang, K. Grauman, and F. Sha. Learning a Tree of Metrics with Disjoint Visual Features. In NIPS, 2011.
8. S. J. Hwang, F. Sha, and K. Grauman. Sharing features between objects and their attributes. In CVPR, 2011.
9. L. Jacob, F. Bach, and J.P. Vert. Clustered Multi-Task Learning: A Convex Formulation. In NIPS, 2008.
10. Z. Kang, K. Grauman, and F. Sha. Learning with whom to share in multi-task feature learning. In ICML.
11. S. Kim and E. Xing. Tree-guided group lasso for multi-response regression with structured sparsity, with an application to eQTL mapping. In AAS, 2012.
12. A. Kovashka, D. Parikh, and K. Grauman. WhittleSearch: Image Search with Relative Attribute Feedback. In CVPR, 2012.
13. A. Kumar and H. Daume III. Learning task grouping and overlap in multi-task learning. In ICML, 2012.
14. N. Kumar, P. N. Belhumeur, and S. K. Nayar. Facetracer: A Search Engine for Large Collections of Images with Faces. In ECCV, 2008.
15. L. Xiao and D. Zhou and M. Wu. Hierarchical Classification via Orthogonal Transfer. In ICML, 2011.
16. C. Lampert. Semantic Attributes for Object Categorization (slides). http://ist.ac.at/chl/talks/lampert-vrml2011b.pdf, 2011.
17. C. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
18. D. Mahajan, S. Sellamanickam, and V. Nair. A joint learning framework for attribute models and object descriptions. In ICCV, 2011.
19. S. Parameswaran and K. Weinberger. Large margin multi-task metric learning. In NIPS, 2010.
20. B. Romera-Paredes, A. Argyriou, N. Bianchi-Berthouze, and M. Pontil. Exploiting unrelated tasks in multi-task learning. In AIS-TATS, 2012.
21. B. Saleh, A. Farhadi, and A. Elgammal. Object-Centric Anomaly Detection by Attribute-Based Reasoning. In CVPR, 2013.
22. W. Scheirer, N. Kumar, P.N. Belhumeur, and T.E. Boult. MultiAttribute Spaces: Calibration for Attribute Fusion and Similarity Search. In CVPR, 2012.
23. A. Shrivastava, S. Singh, and A. Gupta. Constrained semi-supervised learning using attributes and comparative attributes. In ECCV, 2012.
24. B. Siddiquie, R. Feris, and L. Davis. Image Ranking and Retrieval Based on Multi-Attribute Queries. In CVPR, 2011.
25. F. Song, X. Tan, and S. Chen. Exploiting relationship between attributes for improved face verification. In BMVC, 2011.
26. R. Tibshirani. Regression shrinkage and selection via the lasso. In RSS Series B, 1996.
27. A. Torralba, K. Murphy, and W. Freeman. Sharing visual features for multiclass and multiview object detection. In PAMI, 2007.
28. C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie. The Caltech-UCSD Birds-200-2011 Dataset. 2011.
29. G. Wang and D. Forsyth. Joint learning of visual attributes, object classes and visual saliency. In CVPR, 2009.
30. Y. Wang and G. Mori. A discriminative latent model of object classes and attributes. In ECCV, 2010.
31. F. Yu, L. Cao, R. Feris, J. Smith, and S. Chang. Designing category-level attributes for discriminative visual recognition. In CVPR, 2013.
32. M. Yuan and Y. Lin. Model selection and estimation in regression with grouped variables. In RSS Series B, 2006.
33. Y. Zhou, R. Jin, and S.C.H. Hoi. Exclusive lasso for multi-task feature selection. In AISTATS, 2010.