Im2Text: Describing images using 1 million captioned photographs

Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011, NIPS 2011

Volumn , Issue , 2011, Pages

  Ordonez, Vicente ^a   Kulkarni, Girish ^a   Berg, Tamara L ^a  

^a STONY BROOK UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DESCRIPTION METHOD; IMAGE CAPTIONING; IMAGE CONTENT; IMAGE DESCRIPTIONS; NONPARAMETRIC METHODS; OBJECTIVE PERFORMANCE MEASURES; PHOTO COLLECTIONS; SIMPLE++; STATE OF THE ART;

EID: 85162522202     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (30)

1. K. Barnard, P. Duygulu, N. de Freitas, D. Forsyth, D. Blei, and M. Jordan. Matching words and pictures. Journal of Machine Learning Research, 3:1107-1135, 2003.
2. T. Berg, A. Berg, J. Edwards, M. Maire, R. White, E. Learned-Miller, Y. Teh, and D. Forsyth. Names and faces. In CVPR, 2004.
3. L. Bourdev, S. Maji, T. Brox, and J. Malik. Detecting people using mutually consistent poselet activations. In ECCV, 2010.
4. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
5. 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.
6. P. Duygulu, K. Barnard, N. de Freitas, and D. Forsyth.Object recognition as machine translation. In ECCV, 2002.
7. M. Everingham, L. Van Gool, C. K. I. Williams, J. Winn, and A. Zisserman. The PASCAL VisualObject Classes Challenge 2010 (VOC2010) Results. http://www.pascalnetwork.org/challenges/VOC/voc2010/workshop/index.html.
8. A. Farhadi, I. Endres, D. Hoiem, and D. A. Forsyth. Describing objects by their attributes. In CVPR, 2009.
9. A. Farhadi, M. Hejrati, A. Sadeghi, P. Young, C. Rashtchian, J. Hockenmaier, and D. A. Forsyth. Every picture tells a story: generating sentences for images. In ECCV, 2010.
10. P. F. Felzenszwalb, R. B. Girshick, and D. McAllester. Discriminatively trained deformable part models, release 4. http://people.cs.uchicago.edu/pff/ latent-release4/.
11. Y. Feng and M. Lapata. How many words is a picture worth? automatic caption generation for news images. In Proc. of the Assoc. for Computational Linguistics, ACL '10, pages 1239-1249, 2010.
12. V. Ferrari and A. Zisserman. Learning visual attributes. In NIPS, 2007.
13. J. Hays and A. A. Efros. im2gps: estimating geographic information from a single image. In Proceedings of the IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), 2008.
14. D. Hoiem, A. A. Efros, and M. Hebert. Recovering surface layout from an image. Int. J. Comput. Vision, 75:151-172,October 2007.
15. G. Kulkarni, V. Premraj, S. Dhar, S. Li, Y. Choi, A. C. Berg, and T. L. Berg. Babytalk: Understanding and generating simple image descriptions. In CVPR, 2011.
16. N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar. Attribute and simile classifiers for face verification. In ICCV, 2009.
17. C. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
18. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching. In CVPR, June 2006.
19. W. Li, W. Xu, M. Wu, C. Yuan, and Q. Lu. Extractive summarization using inter- and intra- event relevance. In Int Conf on Computational Linguistics, 2006.
20. E. P. X. Li-Jia Li, Hao Su and L. Fei-Fei.Object bank: A high-level image representation for scene classification and semantic feature sparsification. In Neural Information Processing Systems (NIPS), Vancouver, Canada, December 2010.
21. S. Maji, L. Bourdev, and J. Malik. Action recognition from a distributed representation of pose and appearance. In CVPR, 2011.
22. R. Mihalcea. Language independent extractive summarization. In National Conference on Artificial Intelligence, pages 1688-1689, 2005.
23. A. Nenkova, L. Vanderwende, and K. McKeown. A compositional context sensitive multi-document summarizer: exploring the factors that influence summarization. In SIGIR, 2006.
24. K. Papineni, S. Roukos, T. Ward, and W. jing Zhu. Bleu: a method for automatic evaluation of machine translation. pages 311-318, 2002.
25. D. R. Radev and T. Allison. Mead - a platform for multidocument multilingual text summarization. In Int Conf on Language Resources and Evaluation, 2004.
26. J. Tighe and S. Lazebnik. Superparsing: Scalable nonparametric image parsing with superpixels. In ECCV, 2010.
27. A. Torralba, R. Fergus, andW. Freeman. 80 million tiny images: a large dataset for non-parametric object and scene recognition. PAMI, 30, 2008.
28. K.-F.Wong, M.Wu, andW. Li. Extractive summarization using supervised and semi-supervised learning. In International Conference on Computational Linguistics, pages 985-992, 2008.
29. J. Xiao, J. Hays, K. Ehinger, A.Oliva, and A. Torralba. Sun database: Large-scale scene recognition from abbey to zoo. In CVPR, 2010.
30. B. Yao, X. Yang, L. Lin, M. W. Lee, and S.-C. Zhu. I2t: Image parsing to text description. Proc. IEEE, 98(8), 2010.