Deep convolutional ranking for multilabel image annotation

2nd International Conference on Learning Representations, ICLR 2014 - Conference Track Proceedings

Volumn , Issue , 2014, Pages

  Gong, Yunchao ^a   Jia, Yangqing ^b   Leung, Thomas K ^b   Toshev, Alexander ^b   Ioffe, Sergey ^b  

^a UNIVERSITY OF NORTH CAROLINA   (United States)

^b GOOGLE INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONVOLUTION; DEEP NEURAL NETWORKS; IMAGE ANALYSIS;

MULTI-LABEL; MULTI-LABEL ANNOTATION; PERFORMANCE GAIN; REAL-WORLD; TAGGING PROBLEM; TOP-K RANKINGS; VISUAL FEATURE;

IMAGE ANNOTATION;

EID: 85083950293     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (37)

1. Kobus Barnard and David Forsyth. Learning the semantics of words and pictures. In ICCV, 2001.
2. Tamara Berg and David Forsyth. Animals on the web. CVPR, 2007.
3. Gustavo Carneiro, Antoni B Chan, Pedro J Moreno, and Nuno Vasconcelos. Supervised learning of semantic classes for image annotation and retrieval. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 29(3):394–410, 2007.
4. Tat-Seng Chua, Jinhui Tang, Richang Hong, Haojie Li, Zhiping Luo, and Yan-Tao. Zheng. Nus-wide: A real-world web image database from national university of singapore. In Proc. of ACM Conf. on Image and Video Retrieval (CIVR’09), Santorini, Greece., July 8-10, 2009.
5. Jeffrey Dean, Greg Corrado, Rajat Monga, Kai Chen, Matthieu Devin, Quoc Le, Mark Mao, Marc’Aurelio Ranzato, Andrew Senior, Paul Tucker, Ke Yang, and Andrew Ng. Large scale distributed deep networks. In P. Bartlett, F.C.N. Pereira, C.J.C. Burges, L. Bottou, and K.Q. Weinberger, editors, Advances in Neural Information Processing Systems 25, pages 1232–1240, 2012.
6. Jia Deng, W. Dong, R. Socher, Lijia Li, Kai Li, and Li Fei-Fei. Imagenet: A large-scale hierarchical image database. CVPR, 2009.
7. Jeff Donahue, Yangqing Jia, Oriol Vinyals, Judy Hoffman, Ning Zhang, Eric Tzeng, and Trevor Darrell. Decaf: A deep convolutional activation feature for generic visual recognition. arXiv preprint arXiv:1310.1531, 2013.
8. Pinar Duygulu, Kobus Barnard, Nando de Freitas, and David Forsyth. Object recognition as machine translation: Learning a lexicon for a fixed image vocabulary. In ECCV, 2002.
9. R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.-J. Lin. Liblinear: A library for large linear classification. JMLR, 2008.
10. Rob Fergus, Antonio Torralba, and Yair Weiss. Semi-supervised learning in gigantic image collections. NIPS, 2009.
11. Yunchao Gong, Qifa Ke, Michael Isard, and Svetlana Lazebnik. A multi-view embedding space for internet images, tags, and their semantics. IJCV, 2013.
12. Yunchao Gong and Svetlana Lazebnik. Iterative quantization: An procrustean approach to learning binary codes. CVPR, 2011.
13. Ian Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, and Yoshua Bengio. Maxout networks. ICML, 2013.
14. M. Guillaumin, T. Mensink, J. Verbeek, and C. Schmid. Tagprop: Discriminative metric learning in nearest neighbor models for image auto-annotation. ICCV, 2009.
15. Matthieu Guillaumin, Jakob Verbeek, and Cordelia Schmid. Multimodal semi-supervised learning for image classification. CVPR, 2010.
16. Geoffrey Hinton, Nitish Srivastava, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. Improving neural networks by preventing co-adaptation of feature detectors. Arxiv, 2012.
17. What is the best multi-stage architecture for object recognition? K. jarrett and k. kavukcuoglu and m. a. ranzato and y. lecun. CVPR, 2009.
18. HervJégou, M. Douze, Cordelia Schmid, and Patrick Perez. Aggregating local descriptors into a compact image representation. CVPR, 2010.
19. Thorsten Joachims. Optimizing search engines using clickthrough data. In Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD ’02, pages 133–142, New York, NY, USA, 2002. ACM.
20. Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. Imagenet classification with deep convolutional neural networks. NIPS, 2012.
21. Svetlana Lazebnik, Cordelia Schmid, and Jean Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. CVPR, 2006.
22. Y. LeCun, B. Boser, J.S. Denker, D. Henderson, R.E. Howard, W. Hubbard, and L.D. Jackel. Handwritten digit recognition with a back-propagation network. NIPS, 1990.
23. H. Lee, R. Grosse, R. Ranganath, and A.Y. Ng. Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations. ICML, 2009.
24. David G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 2004.
25. Ameesh Makadia, Vladimir Pavlovic, and Sanjiv Kumar. A new baseline for image annotation. In ECCV, 2008.
26. F. Monay and D. Gatica-Perez. Plsa-based image autoannotation: Constraining the latent space. In ACM Multimedia, 2004.
27. Aude Oliva and Antonio Torralba. Modeling the shape of the scene: a holistic representation of the spatial envelope. IJCV, 2001.
28. Florent Perronnin and Christopher R. Dance. Fisher kernels on visual vocabularies for image categorization. CVPR, 2007.
29. A. Quattoni, M. Collins, and T. Darrell. Learning visual representations using images with captions. CVPR, 2007.
30. N. Rasiwasia, PJ Moreno, and N. Vasconcelos. Bridging the gap: Query by semantic example. IEEE Transactions on Multimedia, 2007.
31. Koen E. A. van de Sande, Theo Gevers, and Cees G. M. Snoek. Evaluating color descriptors for object and scene recognition. PAMI, 2010.
32. Li Wan, Matt Zeiler, Sixin Zhang, Yann Lecun, and Rob Fergus. Regularization of neural networks using dropconnect. ICML, 2013.
33. Jinjun Wang, Jianchao Yang, Kai Yu, Fengjun Lv, Thomas Huang, and Yihong Gong. Locality-constrained linear coding for image classification. CVPR, 2010.
34. Jason Weston, Samy Bengio, and Nicolas Usunier. Wsabie: Scaling up to large vocabulary image annotation. In IJCAI, 2011.
35. Jianxiong Xiao, James Hays, Krista Ehinger, Aude Oliva, and Antonio Torralba. Sun database: Large-scale scene recognition from abbey to zoo. CVPR, 2010.
36. Jianchao Yang, Kai Yu, Yihong Gong, and Thomas Huang. Linear spatial pyramid matching uisng sparse coding for image classification. CVPR, 2009.
37. Matt Zeiler and Rob Fergus. Stochastic pooling for regularization of deep convolutional neural networks. ICLR, 2013.