Multi-fold MIL training for weakly supervised object localization

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 2409-2416

  Cinbis, Ramazan Gokberk ^a   Verbeek, Jakob ^a   Schmid, Cordelia ^a  

^a UNIV GRENOBLE ALPES   (France)

Author keywords

object detection; object localization; weakly supervised training

Indexed keywords

COMPUTER VISION; IMAGE ENHANCEMENT; LEARNING SYSTEMS; LOCATION; OBJECT RECOGNITION;

DETECTION PERFORMANCE; EXPERIMENTAL EVALUATION; MULTIPLE INSTANCE LEARNING; OBJECT CATEGORIES; OBJECT LOCALIZATION; SUPERVISED TRAININGS; WEAKLY SUPERVISED LEARNING; WEAKLY SUPERVISED TRAININGS;

OBJECT DETECTION;

EID: 84911376072     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.309     Document Type: Conference Paper

References (33)

1. B. Alexe, T. Deselaers, and V. Ferrari. What is an object? In CVPR, 2010.
2. S. Bagon, O. Brostovski, M. Galun, and M. Irani. Detecting and sketching the common. In CVPR, 2010.
3. T. Berg, A. Berg, J. Edwards, M. Maire, R. White, Y. Teh, E. Learned-Miller, and D. Forsyth. Names and faces in the news. In CVPR, 2004.
4. M. Blaschko, A. Vedaldi, and A. Zisserman. Simultaneous object detection and ranking with weak supervision. In NIPS, 2010.
5. D. Blei, A. Ng, and M. Jordan. Latent Dirichlet allocation. JMLR, 3:993-1022, 2003.
6. K. Chatfield, V. Lempitsky, A. Vedaldi, and A. Zisserman. The devil is in the details: an evaluation of recent feature encoding methods. In BMVC, 2011.
7. Q. Chen, Z. Song, R. Feris, A. Datta, L. Cao, Z. Huang, and S. Yan. Efficient maximum appearance search for large-scale object detection. In CVPR, 2013.
8. O. Chum and A. Zisserman. An exemplar model for learning object classes. In CVPR, 2007.
9. R. Cinbis, J. Verbeek, and C. Schmid. Segmentation driven object detection with Fisher vectors. In ICCV, 2013.
10. D. Crandall and D. Huttenlocher. Weakly supervised learning of part-based spatial models for visual object recognition. In ECCV, 2006.
11. T. Deselaers, B. Alexe, and V. Ferrari. Weakly supervised localization and learning with generic knowledge. IJCV, 100(3):257-293, 2012.
12. T. Dietterich, R. Lathrop, and T. Lozano-Pérez. Solving the multiple instance problem with axis-parallel rectangles. Artificial Intelligence, 89(1-2):31-71, 1997.
13. M. Everingham, J. Sivic, and A. Zisserman. Taking the bite out of automatic naming of characters in TV video. Image and Vision Computing, 27(5):545-559, 2009.
14. M. Everingham, L. van Gool, C. Williams, J. Winn, and A. Zisserman. The Pascal visual object classes (VOC) challenge. IJCV, 88(2):303-338, June 2010.
15. P. Felzenszwalb, R. Grishick, D. McAllester, and D. Ra-manan. Object detection with discriminatively trained part based models. PAMI, 32(9), 2010.
16. R. B. Girshick, P. F. Felzenszwalb, and D. McAllester. Discriminatively trained deformable part models, release 5. http://people.cs.uchicago.edu/rbg/latent-release5.
17. C. Gu, P. Arbeláez, Y. Lin, K. Yu, and Malik. Multi-component models for object detection. In ECCV, 2012.
18. C. Lampert, M. Blaschko, and T. Hofmann. Efficient subwindow search: a branch and bound framework for object localization. PAMI, 31(12):2129-2142, 2009.
19. M. Nguyen, L. Torresani, F. de la Torre, and C. Rother. Weakly supervised discriminative localization and classification: a joint learning process. In ICCV, 2009.
20. M. Pandey and S. Lazebnik. Scene recognition and weakly supervised object localization with deformable part-based models. In ICCV, 2011.
21. O. Parkhi, A. Vedaldi, C. Jawahar, and A. Zisserman. The truth about cats and dogs. In ICCV, 2011.
22. A. Prest, C. Leistner, J. Civera, C. Schmid, and V. Ferrari. Learning object class detectors from weakly annotated video. In CVPR, 2012.
23. O. Russakovsky, Y. Lin, K. Yu, and L. Fei-Fei. Object-centric spatial pooling for image classification. In ECCV, 2012.
24. J. Sánchez, F. Perronnin, T. Mensink, and J. Verbeek. Image classification with the Fisher vector: Theory and practice. IJCV, 105(3):222-245, 2013.
25. Z. Shi, T. Hospedales, and T. Xiang. Bayesian joint topic modelling for weakly supervised object localisation. In ICCV, 2013.
26. S. Singh, A. Gupta, and A. Efros. Unsupervised discovery of mid-level discriminative patches. In ECCV, 2012.
27. P. Siva, C. Russell, and T. Xiang. In defence of negative mining for annotating weakly labelled data. In ECCV, 2012.
28. P. Siva, C. Russell, T. Xiang, and L. Agapito. Looking beyond the image: Unsupervised learning for object saliency and detection. In CVPR, 2013.
29. P. Siva and T. Xiang. Weakly supervised object detector learning with model drift detection. In ICCV, 2011.
30. Z. Song, Q. Chen, Z. Huang, Y. Hua, and S. Yan. Contextu-alizing object detection and classification. In CVPR, 2011.
31. J. Uijlings, K. van de Sande, T. Gevers, and A. Smeulders. Selective search for object recognition. IJCV, 104(2):154-171, 2013.
32. J. Verbeek and B. Triggs. Region classification with Markov field aspect models. In CVPR, 2007.
33. S. Vijayanarasimhan and K. Grauman. Large-scale live active learning: Training object detectors with crawled data and crowds. In CVPR, 2011.