3D object representations for fine-grained categorization

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2013, Pages 554-561

  Krause, Jonathan ^a   Stark, Michael ^a,b   Deng, Jia ^a   Fei Fei, Li ^a  

^a Stanford University   (United States)

^b MAX PLANCK INSTITUTE FOR INFORMATICS   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SCIENCE; COMPUTERS; ELECTRICAL ENGINEERING;

3D OBJECT REPRESENTATION; 3D RECONSTRUCTION; BASELINE MATCHING; LOCAL FEATURE; OBJECT CLASS DETECTIONS; SCENE UNDERSTANDING; STATE-OF-THE-ART APPROACH; TRAINING DATA;

THREE DIMENSIONAL;

EID: 84897485170     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCVW.2013.77     Document Type: Conference Paper

References (37)

1. R. Arandjelovic and A. Zisserman. Three things everyone should know to improve object retrieval. In CVPR, 2012.
2. A. Bar-Hillel and D. Weinshall. Subordinate class recognition using relational object models. In NIPS, 2006.
3. L. Bo, X. Ren, and D. Fox. Kernel descriptors for visual recognition. NIPS, 2010.
4. L. Bourdev and J. Malik. Poselets: Body part detectors trained using 3d human pose annotations. In ICCV, 2009.
5. D. Cline, S. Jeschke, K. White, A. Razdan, and P. Wonka. Dart throwing on surfaces. In Eurographics, 2009.
6. G. Csurka, C. R. Dance, L. Fan, J.Willamowski, and C. Bray. Visual categorization with bags of keypoints. In ECCV, 2004.
7. N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
8. J. Deng, J. Krause, and L. Fei-Fei. Fine-grained crowdsourcing for fine-grained recognition. In CVPR, 2013.
9. 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.
10. P. F. Felzenszwalb, R. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained part based models. PAMI, 2010.
11. A. Gupta, A. A. Efros, and M. Hebert. Blocks world revisited: Image understanding using qualitative geometry and mechanics. In ECCV'10.
12. P. Gupta, S. S. Arrabolu, M. Brown, and S. Savarese. Video scene categorization by 3d hierarchical histogram matching. In ICCV, 2009.
13. R. I. Hartley and A. Zisserman. Multiple View Geometry in Computer Vision. Cambridge University Press, second edition, 2004.
14. D. Hoiem, A. Efros, and M. Hebert. Putting objects in perspective. IJCV, 2008.
15. P. G. Ipeirotis, F. Provost, and J. Wang. Quality management on amazon mechanical turk. In WS ACM SIGKDD, 2010.
16. N. Kumar, P. N. Belhumeur, A. Biswas, D. W. Jacobs, W. J. Kress, I. C. Lopez, and J. V. Soares. Leafsnap: A computer vision system for automatic plant species identification. In ECCV. 2012.
17. S. Lazebnik, C. Schmid, and J. Ponce. Beyond bags of features: Spatial pyramid matching for recognizing natural scene categories. In CVPR, 2006.
18. J. Liebelt and C. Schmid. Multi-view object class detection with a 3d geometric model. In CVPR, 2010.
19. J. Liu, A. Kanazawa, D. Jacobs, and P. Belhumeur. Dog breed classification using part localization. In ECCV. 2012.
20. D. Lowe. Distinctive image features from scale invariant keypoints. IJCV, 2004.
21. T. Malisiewicz, A. Gupta, and A. A. Efros. Ensemble of exemplarsvms for object detection and beyond. In ICCV, 2011.
22. M.-E. Nilsback and A. Zisserman. Automated flower classification over a large number of classes. In ICVGIP, 2008.
23. O. M. Parkhi, A. Vedaldi, C. Jawahar, and A. Zisserman. The truth about cats and dogs. In ICCV, 2011.
24. B. Pepik, P. Gehler, M. Stark, and B. Schiele. 3d2pm - 3d deformable part models. In ECCV, 2012.
25. C. Redondo-Cabrera, R. J. Lopez-Sastre, J. Acevedo-Rodríguez, and S. Maldonado-Bascón. Surfing the point clouds: Selective 3d spatial pyramids for category-level object recognition. In CVPR, 2012.
26. S. Savarese and L. Fei-Fei. 3D generic object categorization, localization and pose estimation. In ICCV, 2007.
27. M. Stark, J. Krause, B. Pepik, D. Meger, J. J. Little, B. Schiele, and D. Koller. Fine-grained categorization for 3d scene understanding. In BMVC, 2012.
28. H. Su, J. Deng, and L. Fei-Fei. Crowdsourcing annotations for visual object detection. In AAAI-WS, 2012.
29. C. Wah, S. Branson, P. Perona, and S. Belongie. Multiclass recognition and part localization with humans in the loop. In ICCV'11.
30. J. Wang, J. Yang, K. Yu, F. Lv, T. Huang, and Y. Gong. Localityconstrained linear coding for image classification. In CVPR'10.
31. C. Wu, S. Agarwal, B. Curless, and S. M. Seitz. Multicore bundle adjustment. In CVPR, 2011.
32. Y. Xiang and S. Savarese. Estimating the aspect layout of object categories. In CVPR, 2012.
33. B. Yao, G. Bradski, and L. Fei-Fei. A codebook- and annotation-free approach for fine-grained image categorization. In CVPR'12.
34. B. Yao, A. Khosla, and L. Fei-Fei. Combining randomization and discrimination for fine-grained image categorization. In CVPR'11.
35. C. Zauner. Implementation and benchmarking of perceptual image hash functions. Master's thesis, Austria.
36. N. Zhang, R. Farrell, and T. Darrell. Pose pooling kernels for subcategory recognition. In CVPR, 2012.
37. M. Z. Zia, M. Stark, B. Schiele, and K. Schindler. Revisiting 3d geometric models for accurate object shape and pose. In 3dRR11.