From virtual to reality: Fast adaptation of virtual object detectors to real domains

BMVC 2014 - Proceedings of the British Machine Vision Conference 2014

Volumn , Issue , 2014, Pages

  Sun, Baochen ^a   Saenko, Kate ^a  

^a University of Massachusetts Lowell   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGE TEXTURE; LARGE DATASET; OBJECT RECOGNITION; RENDERING (COMPUTER GRAPHICS); STATISTICAL TESTS; TEXTURES; THREE DIMENSIONAL COMPUTER GRAPHICS; VIRTUAL ADDRESSES; VIRTUAL REALITY;

BENCHMARK DOMAINS; FAST ADAPTATIONS; GROWING DEMAND; MANUAL LABELING; MULTICATEGORY; OBJECT CATEGORIES; VIRTUAL DATA; VIRTUAL OBJECTS;

OBJECT DETECTION;

EID: 85031103438     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.5244/c.28.82     Document Type: Conference Paper

References (28)

1. Y. Aytar and A. Zisserman. Tabula rasa: Model transfer for object category detection. In IEEE International Conference on Computer Vision, 2011.
2. Y. Aytar and A. Zisserman. Enhancing exemplar svms using part level transfer regularization. In British Machine Vision Conference, 2012.
3. Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. Imagenet: A large-scale hierarchical image database. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages 248-255. IEEE, 2009.
4. Mark Everingham, Luc Van Gool, Christopher KI Williams, John Winn, and Andrew Zisserman. The pascal visual object classes (voc) challenge. International journal of computer vision, 88(2):303-338, 2010.
5. Pedro F Felzenszwalb, Ross B Girshick, David McAllester, and Deva Ramanan. Object detection with discriminatively trained part-based models. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 32(9):1627-1645, 2010.
6. Andreas Geiger, Philip Lenz, and Raquel Urtasun. Are we ready for autonomous driving? the kitti vision benchmark suite. In Conference on Computer Vision and Pattern Recognition (CVPR), 2012.
7. Daniel Goehring, Judy Hoffman, Erik Rodner, Kate Saenko, and Trevor Darrell. Interactive adaptation of real-time object detectors. In International Conference on Robotics and Automation (ICRA), 2014.
8. B. Gong, Y. Shi, F. Sha, and K. Grauman. Geodesic flow kernel for unsupervised domain adaptation. In Proc. CVPR, 2012.
9. R. Gopalan, R. Li, and R. Chellappa. Domain adaptation for object recognition: An unsupervised approach. In Proc. ICCV, 2011.
10. Bharath Hariharan, Jitendra Malik, and Deva Ramanan. Discriminative decorrelation for clustering and classification. In Computer Vision-ECCV 2012, pages 459-472. Springer, 2012.
11. Judy Hoffman, Erik Rodner, Jeff Donahue, Kate Saenko, and Trevor Darrell. Efficient learning of domain-invariant image representations. In International Conference on Representation Learning, arXiv:1301.3224, 2013.
12. A. Khosla, T. Zhou, T. Malisiewicz, A. Efros, and A. Torralba. Undoing the damage of dataset bias. In Proceedings of the 12th European conference on Computer Vision, 2012.
13. Brian Kulis, Kate Saenko, and Trevor Darrell. What you saw is not what you get: Domain adaptation using asymmetric kernel transforms. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 1785-1792. IEEE, 2011.
14. J. Liebelt and C. Schmid. Multi-view object class detection with a 3d geometric model. In Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on, 2010.
15. J. Liebelt, C. Schmid, and Klaus Schertler. Viewpoint-independent object class detection using 3d feature maps. In Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on, 2008.
16. Tomasz Malisiewicz, Abhinav Gupta, and Alexei A Efros. Ensemble of exemplar-svms for object detection and beyond. In Computer Vision (ICCV), 2011 IEEE International Conference on, pages 89-96. IEEE, 2011.
17. Ramakant Nevatia and Thomas O. Binford. Description and recognition of curved objects. Artificial Intelligence, 8(1):77-98, 1977.
18. B. Pepik, M. Stark, P. Gehler, and B. Schiele. Teaching 3d geometry to deformable part models. In Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on, 2012.
19. Daniel Ponsa, David Geronimo, Antonio M. Lopez, Javier Marin, and David Vazquez. Virtual and real world adaptationfor pedestrian detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36(4):797-809, 2014. ISSN 0162-8828.
20. Kate Saenko, Brian Kulis, Mario Fritz, and Trevor Darrell. Adapting visual category models to new domains. In Computer Vision-ECCV 2010, pages 213-226. Springer, 2010.
21. Silvio Savarese and Li Fei-Fei. View synthesis for recognizing unseen poses of object classes. In David Forsyth, Philip Torr, and Andrew Zisserman, editors, Computer Vision U ECCV 2008, volume 5304 of Lecture Notes in Computer Science, pages 602-615. Springer Berlin Heidelberg, 2008.
22. Michael Stark, Michael Goesele, and Bernt Schiele. Back to the future: Learning shape models from 3d cad data. In Proc. BMVC, pages 106.1-11, 2010. ISBN 1-901725-40- 5. doi:10.5244/C.24.106.
23. Min Sun, Hao Su, S. Savarese, and Li Fei-Fei. A multi-view probabilistic model for 3d object classes. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, 2009.
24. Antonio Torralba and Alexei A Efros. Unbiased look at dataset bias. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 1521-1528. IEEE, 2011.
25. Yu Xiang, Roozbeh Mottaghi, and Silvio Savarese. Beyond pascal: A benchmark for 3d object detection in the wild. In IEEE Winter Conference on Applications of Computer Vision (WACV), 2014.
26. Jiaolong Xu, D. Vazquez, S. Ramos, A.M. Lopez, and D. Ponsa. Adapting a pedestrian detector by boosting lda exemplar classifiers. In Computer Vision and Pattern Recognition Workshops (CVPRW), 2013 IEEE Conference on, June 2013.
27. Jiaolong Xu, Sebastian Ramos, David Vazquez, and Antonio Lopez. Domain adaptation of deformable part-based models. in submission, 2014. URL http://refbase.cvc.uab.es/files/xrv2013.pdf.
28. J. Yang, R. Yan, and A. G. Hauptmann. Cross-domain video concept detection using adaptive svms. ACM Multimedia, 2007.