Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes

Proceedings - 2017 IEEE Winter Conference on Applications of Computer Vision, WACV 2017

Volumn , Issue , 2017, Pages 944-952

  Long, Yang ^a   Liu, Li ^b   Shao, Ling ^b  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

^b UNIVERSITY OF EAST ANGLIA   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTICS;

FINE GRAINED; HIGH QUALITY; NOVEL ALGORITHM; STATE OF THE ART; SUPERVISED CLASSIFICATION; TRAINING DATA; VISUAL DIFFERENCES; VISUAL FEATURE;

COMPUTER VISION;

EID: 85020195882     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WACV.2017.110     Document Type: Conference Paper

References (40)

1. Z. Akata, F. Perronnin, Z. Harchaoui, and C. Schmid. Labelembedding for attribute-based classification. In CVPR, 2013.
2. Z. Akata, S. Reed, D. Walter, H. Lee, and B. Schiele. Evaluation of output embeddings for fine-grained image classification. In CVPR, 2015.
3. Z. Al-Halah, T. Gehrig, and R. Stiefelhagen. Learning semantic attributes via a common latent space. In VISAPP, 2014.
4. Z. Cai, L. Liu, M. Yu, and L. Shao. Latent structure preserving hashing. In BMVC, 2015.
5. S. Changpinyo, W.-L. Chao, B. Gong, and F. Sha. Synthesized classifiers for zero-shot learning. In CVPR, 2016.
6. S. Changpinyo, W.-L. Chao, and F. Sha. Predicting visual exemplars of unseen classes for zero-shot learning. arXiv preprint arXiv:1605.08151, 2016.
7. A. Farhadi, I. Endres, D. Hoiem, and D. Forsyth. Describing objects by their attributes. In CVPR, 2009.
8. Y. Fu, T. M. Hospedales, T. Xiang, and S. Gong. Learning multimodal latent attributes. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 36(2):303-316, 2014.
9. D. Jayaraman and K. Grauman. Zero-shot recognition with unreliable attributes. In NIPS, 2014.
10. D. Jayaraman, F. Sha, and K. Grauman. Decorrelating semantic visual attributes by resisting the urge to share. In CVPR, 2014.
11. E. Kodirov, T. Xiang, Z. Fu, and S. Gong. Unsupervised domain adaptation for zero-shot learning. In ICCV, 2015.
12. A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
13. C. H. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
14. C. H. Lampert, H. Nickisch, and S. Harmeling. Attributebased classification for zero-shot visual object categorization. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 36(3):453-465, 2014.
15. H. Larochelle, D. Erhan, and Y. Bengio. Zero-data learning of new tasks. In AAAI, 2008.
16. Y. Long, L. Liu, and L. Shao. Attribute embedding with visual-semantic ambiguity removal for zero-shot learning. In BMVC, 2016.
17. Y. Long, L. Liu, and L. Shao. Attribute embedding with visual-semantic ambiguity removal for zero-shot learning. In BMVC, 2016.
18. Y. Long and L. Shao. Describing unseen classes by exemplars: Zero-shot learning using grouped simile ensemble. In WACV, 2017.
19. Y. Long, F. Zhu, and L. Shao. Recognising occluded multiview actions using local nearest neighbour embedding. Computer Vision and Image Understanding, 144:36-45, 2016.
20. D. Mahajan, S. Sellamanickam, and V. Nair. A joint learning framework for attribute models and object descriptions. In ICCV, 2011.
21. T. Mensink, E. Gavves, and C. Snoek. Costa: Co-occurrence statistics for zero-shot classification. In CVPR, 2014.
22. T. Mensink, J. Verbeek, F. Perronnin, and G. Csurka. Metric learning for large scale image classification: Generalizing to new classes at near-zero cost. In ECCV. 2012.
23. M. Palatucci, D. Pomerleau, G. E. Hinton, and T. M. Mitchell. Zero-shot learning with semantic output codes. In NIPS, 2009.
24. G. Patterson, C. Xu, H. Su, and J. Hays. The sun attribute database: Beyond categories for deeper scene understanding. International Journal of Computer Vision, 108(1-2):59-81, 2014.
25. J. Qin, Y. Wang, L. Liu, J. Chen, and L. Shao. Beyond semantic attributes: Discrete latent attributes learning for zero-shot recognition. IEEE Signal Processing Letters, 23(11):1667-1671, 2016.
26. S. Reed, Z. Akata, B. Schiele, and H. Lee. Learning deep representations of fine-grained visual descriptions. In CVPR, 2016.
27. M. Rohrbach, S. Ebert, and B. Schiele. Transfer learning in a transductive setting. In NIPS, 2013.
28. M. Rohrbach, M. Stark, and B. Schiele. Evaluating knowledge transfer and zero-shot learning in a large-scale setting. In CVPR, 2011.
29. M. Rohrbach, M. Stark, G. Szarvas, I. Gurevych, and B. Schiele. What helps where-And why? semantic relatedness for knowledge transfer. In CVPR, 2010.
30. B. Romera-Paredes and P. Torr. An embarrassingly simple approach to zero-shot learning. In ICML, 2015.
31. L. Shao, L. Liu, and M. Yu. Kernelized multiview projection for robust action recognition. International Journal of Computer Vision, 118(2):115-129, 2016.
32. V. Sharmanska, N. Quadrianto, and C. H. Lampert. Augmented attribute representations. In ECCV. 2012.
33. R. Socher, M. Ganjoo, C. D. Manning, and A. Ng. Zero-shot learning through cross-modal transfer. In NIPS, 2013.
34. C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie. The caltech-ucsd birds-200-2011 dataset. Technical Report CNS-TR-2011-001, California Institute of Technology, 2011.
35. Y. Xian, Z. Akata, G. Sharma, Q. Nguyen, M. Hein, and B. Schiele. Latent embeddings for zero-shot classification. In CVPR, 2016.
36. F. Yu, L. Cao, R. Feris, J. Smith, and S.-F. Chang. Designing category-level attributes for discriminative visual recognition. In CVPR, 2013.
37. M. Yu, L. Liu, and L. Shao. Structure-preserving binary representations for rgb-d action recognition. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 38(8):1651-1664, 2016.
38. X. Yu and Y. Aloimonos. Attribute-based transfer learning for object categorization with zero/one training example. In ECCV. 2010.
39. Z. Zhang and V. Saligrama. Zero-shot learning via semantic similarity embedding. In ICCV, 2015.
40. Z. Zhang and V. Saligrama. Zero-shot learning via joint latent similarity embedding. In CVPR, 2016.