Fine-grained categorization by alignments

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2013, Pages 1713-1720

  Gavves, E ^a   Fernando, B ^b   Snoek, C G M ^a   Smeulders, A W M ^a,c   Tuytelaars, T ^b  

^a UNIVERSITY OF AMSTERDAM   (Netherlands)

^b UNIVERSITY OF LEUVEN   (Belgium)

^c CWI   (Netherlands)

Author keywords

fine grained categorization

Indexed keywords

DATA PROCESSING; IMAGE SEGMENTATION;

FINE GRAINED; FINE-GRAINED CATEGORIZATION; FISHER VECTORS; HUMAN INTERACTIONS; ORIENTED FEATURES; POPULAR MATCHING; TEST IMAGES; TRAINING IMAGE;

ALIGNMENT;

EID: 84898802327     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2013.215     Document Type: Conference Paper

References (34)

1. T. Berg and P. N. Belhumeur. POOF: Part-based one-vs-one features for fine-grained categorization, face verification, and attribute estimation. In CVPR, 2013.
2. L. Bo, X. Ren, and D. Fox. Kernel descriptors for visual recognition. In NIPS, 2010.
3. S. Branson, P. Perona, and S. Belongie. Strong supervision from weak annotation: Interactive training of deformable part models. In ICCV, 2011.
4. S. Branson, C. Wah, F. Schroff, B. Babenko, P. Welinder, P. Perona, and S. Belongie. Visual recognition with humans in the loop. In ECCV, 2010.
5. Y. Chai, V. Lempitsky, and A. Zisserman. Bicos: A bi-level cosegmentation method for image classification. In ICCV, 2011.
6. Y. Chai, E. Rahtu, V. Lempitsky, L. Van Gool, and A. Zisserman. Tricos: a tri-level class-discriminative co-segmentation method for image classification. In ECCV, 2012.
7. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
8. 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.
9. K. Duan, D. Parikh, D. Crandall, and K. Grauman. Discovering localized attributes for fine-grained recognition. In CVPR, 2012.
10. R. Farrell, O. Oza, N. Zhang, V. I. Morariu, T. Darrell, and L. S. Davis. Birdlets: Subordinate categorization using volumetric primitives and pose-normalized appearance. In ICCV, 2011.
11. P. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part-based models. PAMI, 32(9):1627-1645, 2010.
12. Y. Jia, O. Vinyals, and T. Darrell. Pooling-invariant image feature learning. Technical report, 2013.
13. F. P. Jorge Sanchez and Z. Akata. Fisher vectors for fine-grained visual categorization. In CVPR, 2011.
14. R. Khan, J. Van de Weijer, F. S. Khan, D. Muselet, C. Ducottet, and C. Barat. Discriminative color descriptors. In CVPR, 2013.
15. A. Khosla, N. Jayadevaprakash, B. Yao, and L. Fei-Fei. Novel dataset for fine-grained image categorization. In CVPR, FGVC workshop, 2011.
16. J. Liu, A. Kanazawa, D. Jacobs, and P. Belhumeur. Dog breed classification using part localization. In ECCV, 2012.
17. D. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004.
18. K. Mikolajczyk, T. Tuytelaars, C. Schmid, A. Zisserman, J. Matas, F. Schaffalitzky, T. Kadir, and L. Van Gool. A comparison of affine region detectors. IJCV, 65(1-2):43-72, 2005.
19. M.-E. Nilsback and A. Zisserman. Automated flower classification over a large number of classes. In ICVGIP, 2008.
20. D. Parikh and K. Grauman. Interactive discovery of task-specific nameable attributes. In CVPR, FGVC workshop, 2011.
21. O. M. Parkhi, A. Vedaldi, A. Zisserman, and C. Jawahar. Cats and dogs. In CVPR, 2012.
22. M. Perd́och, O. Chum, and J. Matas. Efficient representation of local geometry for large scale object retrieval. In CVPR, 2009.
23. F. Perronnin, J. Śanchez, and T. Mensink. Improving the fisher kernel for large-scale image classification. In ECCV, 2010.
24. E. Rosch, C. B. Mervis, W. D. Gray, D. M. Johnson, and P. Boyes-Braem. Basic objects in natural categories. Cogn. psych., 8(3):382-439, 1976.
25. C. Rother, V. Kolmogorov, and A. Blake. Grabcut: Interactive foreground extraction using iterated graph cuts. ACM TOG, 23(3):309-314, 2004.
26. S. Shalev-Shwartz, Y. Singer, and N. Srebro. Pegasos: Primal estimated sub-gradient solver for svm. In ICML, 2007.
27. K. Van De Sande, T. Gevers, and C. Snoek. Evaluating color descriptors for object and scene recognition. PAMI, 2010.
28. A. Vedaldi and B. Fulkerson. Vlfeat: An open and portable library of computer vision algorithms. In MM, 2010.
29. C. Wah, S. Branson, P. Perona, and S. Belongie. Multiclass recognition and part localization with humans in the loop. In ICCV, 2011.
30. C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie. The caltech-ucsd birds-200-2011 dataset. Technical report, 2011.
31. S. Yang, L. Bo, J. Wang, and L. Shapiro. Unsupervised template learning for fine-grained object recognition. In NIPS, 2012.
32. B. Yao, G. Bradski, and L. Fei-Fei. A codebook-free and annotationfree approach for fine-grained image categorization. In CVPR, 2012.
33. B. Yao, A. Khosla, and L. Fei-Fei. Combining randomization and discrimination for fine-grained image categorization. In CVPR, 2011.
34. N. Zhang, R. Farrell, and T. Darrell. Pose pooling kernels for subcategory recognition. In CVPR, 2012.