Beyond comparing image pairs: Setwise active learning for relative attributes

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

Volumn , Issue , 2014, Pages 208-215

  Liang, Lucy ^a   Grauman, Kristen ^a  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

Author keywords

active; active learning; attributes; diverse; diversity; learning; rank; ranking; relative; relative attributes; visual; visual attributes

Indexed keywords

LEARNING SYSTEMS; PATTERN RECOGNITION; PERSONNEL TRAINING;

ACTIVE; ACTIVE LEARNING; ATTRIBUTES; DIVERSE; DIVERSITY; LEARNING; RANK; RANKING; RELATIVE; RELATIVE ATTRIBUTES; VISUAL; VISUAL ATTRIBUTES;

LEARNING TO RANK;

EID: 84911365890     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.34     Document Type: Conference Paper

References (38)

1. T. Berg, A. Berg, and J. Shih. Automatic attribute discovery and characterization from noisy web data. In ECCV, 2010.
2. A. Biswas and D. Parikh. Simultaneous active learning of classifirs & attributes via relative feedback. In CVPR, 2013.
3. S. Branson, C. Wah, F. Schroff, B. Babenko, P. Welinder, P. Perona, and S. Be-longie. Visual recognition with humans in the loop. In ECCV, 2010.
4. K. Brinker. Incorporating Diversity in Active Learning with Support Vector Machines. InICML, 2003.
5. K. Brinker. Active learning of label ranking functions. In ICML, 2004.
6. C. Burges, T. Shaked, E. Renshaw, A. Lazier, M. Deeds, N. Hamilton, and G. Hullender. Learning to rank using gradient descent. In ICML, 2005.
7. Z. Cao, T. Qin, T. Liu, M. Tsai, and H. Li. Learning to rank: From pairwise approach to listwise approach. In ICML, 2007.
8. A. Datta, R. Feris, and D. Vaquero. Hierarchical ranking of facial attributes. In Automatic Face and Gesture Recognition Workshops, 2011.
9. P. Donmez and J. Carbonell. Optimizing estimated loss reduction for active sampling in rank learning. In ICML, 2008.
10. A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth. Describing Objects by their Attributes. In CVPR, 2009.
11. V Ferrari and A. Zisserman. Learning Visual Attributes. In NIPS, 2007.
12. A. Frome, Y. Singer, F. Sha, and J. Malik. Learning Globally-Consistent Local Distance Functions for Image Retrieval and Classification. In ICCV, 2007.
13. Y. Hu, M. Li, and N. Yu. Multiple-instance ranking: Learning to rank images for image retrieval. In CVPR, 2008.
14. V Jain and M. Varma. Learning to re-rank: Query-dependent image re-ranking using click data. In WWW, 2011.
15. T. Joachims. Optimizing search engines with clickthrough data. In KDD, 2002.
16. A. Joshi, F Porikli, and N. Papanikolopoulos. Breaking the interactive bottleneck in multi-class classification with active selection and binary feedback. In CVPR, 2010.
17. A. Kovashka, D. Parikh, and K. Grauman. WhittleSearch: Image search with relative attribute feedback. In CVPR, 2012.
18. A. Kovashka, S. Vijayanarasimhan, and K. Grauman. Actively selecting annotations among objects and attributes. In ICCV, 2011.
19. N. Kumar, P. Belhumeur, and S. Nayar. Facetracer: A Search Engine for Large Collections of Images with Faces. In ECCV, 2008.
20. C. Lampert, H. Nickisch, and S. Harmeling. Learning to Detect Unseen Object Classes by Between-Class Attribute Transfer. In CVPR, 2009.
21. S. Li, S. Shan, and X. Chen. Relative forest for attribute prediction. In ACCV, 2012.
22. T. Liu. Learning to rank for information retrieval. Fnd & Trnds in IR, 2009.
23. B. Long, O. Chapelle, Y Zhang, Y Chang, Z. Zheng, and B. Tseng. Active learning for ranking through expected loss optimization. In SIGIR, 2010.
24. S. Ma, S. Sclaroff, and N. Ikizler-Cinbis. Unsupervised learning of discriminative relative visual attributes. In ECCVWksp on Parts and Attributes, 2012.
25. S. Maji. Discovering a lexicon of parts and attributes. In ECCV Workshop on Parts and Attributes, 2012.
26. A. Oliva and A. Torralba. Modeling the Shape of the Scene: A Holistic Representation of the Spatial Envelope. IJCV, 42:145-175, 2001.
27. D. Parikh and K Grauman. Relative Attributes. In ICCV, 2011.
28. G. Patterson and J. Hays. Sun attribute database: Discovering, annotating, and recognizing scene attributes. In CVPR, 2012.
29. S. Rajaram, C. Dagli, N. Petrovic, and T Huang. Diverse active ranking for multimedia search. In CVPR, 2007.
30. A. Shrivastava, S. Singh, and A. Gupta. Constrained semi-supervised learning using attributes and comparative attributes. In ECCV, 2012.
31. B. Siddiquie, R. S. Feris, and L. S. Davis. Image ranking and retrieval based on multi-attribute queries. In CVPR, 2011.
32. O. Tamuz, C. Liu, S. Belongie, O. Shamir, and A. Kalai. Adaptively learning the crowd kernel. In ICML, 2011.
33. X. Tian, D. Tao, X. Hua, and X. Wu. Active reranking for web image search. IEEE Transactions on Image Processing, 2010.
34. S. Tong and D. Koller. Support Vector Machine Active Learning with Applications to Text Classification. In ICML, 2000.
35. S. Vijayanarasimhan and K. Grauman. Large-Scale Live Active Learning: Training Object Detectors with Crawled Data and Crowds. In CVPR, 2011.
36. Z. Xu, R. Akella, and Y Zhang. Incorporating diversity and density in active learning for relevance feedback. In ECIR, 2007.
37. H. Yu. SVM selective sampling for ranking with application to data retrieval. In KDD, 2005.
38. L. Zhao, G. Sukthankar, and R. Sukthankar. Robust active learning using crowdsourced annotations for activity recognition. In HCOMP, 2011.