Relaxing from vocabulary: Robust weakly-supervised deep learning for vocabulary-free image tagging

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2015 International Conference on Computer Vision, ICCV 2015, Issue , 2015, Pages 1985-1993

  Fu, Jianlong ^a,b   Wu, Yue ^c   Mei, Tao ^b   Wang, Jinqiao ^a   Lu, Hanqing ^a   Rui, Yong ^b  

^a INSTITUTE OF AUTOMATION   (China)

^b MICROSOFT RESEARCH   (United States)

^c UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

Author keywords

[No Author keywords available]

Indexed keywords

APPROXIMATION THEORY; BACKPROPAGATION; FEEDBACK; SEMANTICS;

DEEP LEARNING; HUMAN BEING; IMAGE TAGGING; LOW RANK APPROXIMATIONS; OBJECTIVE FUNCTIONS; PERFORMANCE GAIN; RELEVANCE FEEDBACK; TRAINING DATA;

COMPUTER VISION;

EID: 84973896917     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2015.230     Document Type: Conference Paper

References (27)

1. M. Belkin and P. Niyogi. Laplacian eigenmaps and spectral techniques for embedding and clustering. In NIPS, pages 585-591, 2001.
2. V. Bychkovsky, S. Paris, E. Chan, and F. Durand. Learning photographic global tonal adjustment with a database of input / output image pairs. In CVPR, 2011.
3. E. J. Candès, X. Li, Y. Ma, and J. Wright. Robust principal component analysis? J. ACM, 58 (3): 11: 1-11: 37, 2011.
4. X. Chen, A. Shrivastava, and A. Gupta. Neil: Extracting visual knowledge from web data. In ICCV, 2013.
5. J. Deng, A. C. Berg, K. Li, and L. Fei-Fei. What does classifying more than 10, 000 image categories tell us? In ECCV, pages 71-84, 2010.
6. J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei. Imagenet: A large-scale hierarchical image database. In CVPR, 2009.
7. A. FRome, G. Corrado, J. Shlens, S. Bengio, J. Dean, M. Ranzato, and T. Mikolov. Devise: A deep visual-semantic embedding model. In NIPS, 2013.
8. J. Fu, T. Mei, K. Yang, H. Lu, and Y. Rui. Tagging personal photos with transfer deep learning. InWWW, pages 344-354, 2015.
9. J. Fu, J. Wang, Y. Rui, X.-J. Wang, T. Mei, and H. Lu. Image tag refinment with view-dependent concept representations. In IEEE Transactions on CSVT, volume 25, pages 1409-1422, 2015.
10. B. Graham. Spatially-sparse convolutional neural networks. arXiv preprint arXiv: 1409. 6070, 2014.
11. J. Kim and C. D. Scott. Robust kernel density estimation. In JMLR, pages 2529-2565, 2012.
12. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, pages 1106-1114, 2012.
13. J. Larsen, L. N. Andersen, M. Hintz-madsen, and L. K. Hansen. Design of robust neural network classifiers. In ICASSP, pages 1205-1208, 1998.
14. W. Liu, G. Hua, and J. R. Smith. Unsupervised one-class learning for automatic outlier removal. In CVPR, 2014.
15. P. Luo, X. Wang, and X. Tang. Hierarchical face parsing via deep learning. In CVPR, pages 2480-2487, 2012.
16. J. Masci, U. Meier, D. Cireşan, and J. Schmidhuber. Stacked convolutional auto-encoders for hierarchical feature extraction. In ICANN, pages 52-59, 2011.
17. V. Mnih and G. E. Hinton. Learning to label aerial images from noisy data. In ICML, 2012.
18. M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Learning and transferring mid-level image representations using convolutional neural networks. In CVPR, 2014.
19. M. Oquab, L. Bottou, I. Laptev, and J. Sivic. Is object localization for free-weakly-supervised learning with convolutional neural networks. In CVPR, pages 685-694, 2015.
20. D. Rumelhart, G. Hintont, and R. Williams. Learning representations by back-propagating errors. Nature, 323: 533-536, 1986.
21. R. F. Sainbayar Sukhbaatar. Learning from noisy labels with deep neural networks. arXiv preprint arXiv: 1406. 2080, 2014.
22. C. S. K. Divvala, A. Farhadi. Learning everything about anything: Webly-supervised visual concept learning. In CVPR, 2014.
23. P. Vincent, H. Larochelle, I. Lajoie, Y. Bengio, and P.-A. Manzagol. Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion. JMLR, 11: 3371-3408, 2010.
24. J. Wu, Y. Yu, C. Huang, and K. Yu. Deep multiple instance learning for image classification and auto-annotation. In CVPR, pages 3460-3469, 2015.
25. H. Xu, C. Caramanis, and S. Mannor. Outlier-robust PCA: The high-dimensional case. IEEE Transactions on Information Theory, 59 (1): 546-572, 2013.
26. Y. Yang, H. T. Shen, Z. Ma, Z. Huang, and X. Zhou. l2, 1-norm regularized discriminative feature selection for unsupervised learning. In IJCAI, pages 1589-1594, 2011.
27. J. Ye, Z. Zhao, and M. Wu. Discriminative k-means for clustering. In NIPS, 2007.