메뉴 건너뛰기




Volumn 07-12-June-2015, Issue , 2015, Pages 1619-1628

Model recommendation: Generating object detectors from few samples

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION;

EID: 84959250182     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298770     Document Type: Conference Paper
Times cited : (47)

References (58)
  • 2
    • 27844439373 scopus 로고    scopus 로고
    • A framework for learning predictive structures from multiple tasks and unlabeled data
    • R. K. Ando and T. Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data. JMLR, 6:1817-1853, 2005
    • (2005) JMLR , vol.6 , pp. 1817-1853
    • Ando, R.K.1    Zhang, T.2
  • 3
    • 84856675275 scopus 로고    scopus 로고
    • Tabula rasa: Model transfer for object category detection
    • Y. Aytar and A. Zisserman. Tabula rasa: Model transfer for object category detection. In ICCV, 2011
    • (2011) ICCV
    • Aytar, Y.1    Zisserman, A.2
  • 4
    • 84898484392 scopus 로고    scopus 로고
    • Enhancing exemplar svms using part level transfer regularization
    • Y. Aytar and A. Zisserman. Enhancing exemplar svms using part level transfer regularization. In BMVC, 2012
    • (2012) BMVC
    • Aytar, Y.1    Zisserman, A.2
  • 7
    • 84887366030 scopus 로고    scopus 로고
    • Adding unlabeled samples to categories by learned attributes
    • J. Choi, M. Rastegari, A. Farhadi, and L. S. Davis. Adding unlabeled samples to categories by learned attributes. In CVPR, 2013
    • (2013) CVPR
    • Choi, J.1    Rastegari, M.2    Farhadi, A.3    Davis, L.S.4
  • 8
    • 77956006912 scopus 로고    scopus 로고
    • Exploiting hierarchical context on a large database of object categories
    • M. J. Choi, J. J. Lim, A. Torralba, and A. S. Willsky. Exploiting hierarchical context on a large database of object categories. In CVPR, 2010
    • (2010) CVPR
    • Choi, M.J.1    Lim, J.J.2    Torralba, A.3    Willsky, A.S.4
  • 9
    • 84887353231 scopus 로고    scopus 로고
    • Contextual object detection using set-based classification
    • R. G. Cinbis and S. Sclaroff. Contextual object detection using set-based classification. In ECCV, 2012
    • (2012) ECCV
    • Cinbis, R.G.1    Sclaroff, S.2
  • 10
    • 84898774288 scopus 로고    scopus 로고
    • Segmentation driven object detection with fisher vectors
    • R. G. Cinbis, J. Verbeek, and C. Schmid. Segmentation driven object detection with fisher vectors. In ICCV, 2013
    • (2013) ICCV
    • Cinbis, R.G.1    Verbeek, J.2    Schmid, C.3
  • 11
    • 84898771670 scopus 로고    scopus 로고
    • Ensemble projection for semisupervised image classification
    • D. Dai and L. V. Gool. Ensemble projection for semisupervised image classification. In ICCV, 2013
    • (2013) ICCV
    • Dai, D.1    Gool, L.V.2
  • 12
    • 84898936638 scopus 로고    scopus 로고
    • Mid-level visual element discovery as discriminative mode seeking
    • C. Doersch, A. Gupta, and A. A. Efros. Mid-level visual element discovery as discriminative mode seeking. In NIPS, 2013
    • (2013) NIPS
    • Doersch, C.1    Gupta, A.2    Efros, A.A.3
  • 14
    • 77955422240 scopus 로고    scopus 로고
    • Object detection with discriminatively trained partbased models
    • P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained partbased models. TPAMI, 32(9):1627-1645, 2010
    • (2010) TPAMI , vol.32 , Issue.9 , pp. 1627-1645
    • Felzenszwalb, P.F.1    Girshick, R.B.2    McAllester, D.3    Ramanan, D.4
  • 15
    • 84911400494 scopus 로고    scopus 로고
    • Rich feature hierarchies for accurate object detection and semantic segmentation
    • R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014
    • (2014) CVPR
    • Girshick, R.1    Donahue, J.2    Darrell, T.3    Malik, J.4
  • 16
    • 84887395819 scopus 로고    scopus 로고
    • Discriminative decorrelation for clustering and classification
    • B. Hariharan, J. Malik, and D. Ramanan. Discriminative decorrelation for clustering and classification. In ECCV, 2012
    • (2012) ECCV
    • Hariharan, B.1    Malik, J.2    Ramanan, D.3
  • 17
  • 19
    • 0000262562 scopus 로고
    • Hierarchical mixtures of experts and the em algorithm
    • M. I. Jordan and R. A. Jacobs. Hierarchical mixtures of experts and the EM algorithm. Neural computation, 6(2):181-214, 1994
    • (1994) Neural Computation , vol.6 , Issue.2 , pp. 181-214
    • Jordan, M.I.1    Jacobs, R.A.2
  • 20
    • 84887325186 scopus 로고    scopus 로고
    • Blocks that shout: Distinctive parts for scene classification
    • M. Juneja, A. Vedaldi, C. Jawahar, and A. Zisserman. Blocks that shout: Distinctive parts for scene classification. In CVPR, 2013
    • (2013) CVPR
    • Juneja, M.1    Vedaldi, A.2    Jawahar, C.3    Zisserman, A.4
  • 24
    • 77955644905 scopus 로고    scopus 로고
    • Factor in the neighbors: Scalable and accurate collaborative filtering
    • Y. Koren. Factor in the neighbors: Scalable and accurate collaborative filtering. TKDD, 4(1):1-24, 2010
    • (2010) TKDD , vol.4 , Issue.1 , pp. 1-24
    • Koren, Y.1
  • 25
    • 85008044987 scopus 로고    scopus 로고
    • Matrix factorization techniques for recommender systems
    • Y. Koren, R. Bell, and C. Volinsky. Matrix factorization techniques for recommender systems. IEEE Computer, 42(8):30-37, 2009
    • (2009) IEEE Computer , vol.42 , Issue.8 , pp. 30-37
    • Koren, Y.1    Bell, R.2    Volinsky, C.3
  • 26
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012
    • (2012) NIPS
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 27
    • 84897555831 scopus 로고    scopus 로고
    • Stability and hypothesis transfer learning
    • I. Kuzborskij and F. Orabona. Stability and hypothesis transfer learning. In ICML, 2013
    • (2013) ICML
    • Kuzborskij, I.1    Orabona, F.2
  • 28
    • 0001093042 scopus 로고    scopus 로고
    • Algorithms for non-negative matrix factorization
    • D. D. Lee and H. S. Seung. Algorithms for non-negative matrix factorization. In NIPS, 2000
    • (2000) NIPS
    • Lee, D.D.1    Seung, H.S.2
  • 29
    • 85162513516 scopus 로고    scopus 로고
    • Object bank: A highlevel image representation for scene classification & semantic feature sparsification
    • L.-J. Li, H. Su, E. P. Xing, and F.-F. Li. Object bank: A highlevel image representation for scene classification & semantic feature sparsification. In NIPS, 2010
    • (2010) NIPS
    • Li, L.-J.1    Su, H.2    Xing, E.P.3    Li, F.-F.4
  • 30
    • 85162555049 scopus 로고    scopus 로고
    • Transfer learning by borrowing examples for multiclass object detection
    • J. J. Lim, R. Salakhutdinov, and A. Torralba. Transfer learning by borrowing examples for multiclass object detection. In NIPS, 2011
    • (2011) NIPS
    • Lim, J.J.1    Salakhutdinov, R.2    Torralba, A.3
  • 31
    • 85007196229 scopus 로고    scopus 로고
    • Self-explanatory sparse representation for image classification
    • B.-D. Liu, Y.-X. Wang, B. Shen, Y.-J. Zhang, and M. Hebert. Self-explanatory sparse representation for image classification. In ECCV, 2014
    • (2014) ECCV
    • Liu, B.-D.1    Wang, Y.-X.2    Shen, B.3    Zhang, Y.-J.4    Hebert, M.5
  • 32
    • 84875278020 scopus 로고    scopus 로고
    • Learning dictionary on manifolds for image classification
    • B.-D. Liu, Y.-X. Wang, Y.-J. Zhang, and B. Shen. Learning dictionary on manifolds for image classification. PR, 46(7):1879-1890, 2013
    • (2013) PR , vol.46 , Issue.7 , pp. 1879-1890
    • Liu, B.-D.1    Wang, Y.-X.2    Zhang, Y.-J.3    Shen, B.4
  • 33
    • 84863411575 scopus 로고    scopus 로고
    • Ensemble of exemplar-svms for object detection and beyond
    • T. Malisiewicz, A. Gupta, and A. A. Efros. Ensemble of exemplar-svms for object detection and beyond. In ICCV, 2011
    • (2011) ICCV
    • Malisiewicz, T.1    Gupta, A.2    Efros, A.A.3
  • 35
  • 37
    • 84959201998 scopus 로고    scopus 로고
    • Watch and learn: Semi-supervised learning of object detectors from videos
    • I. Misra, A. Shrivastava, and M. Hebert. Watch and learn: Semi-supervised learning of object detectors from videos. In CVPR, 2015
    • (2015) CVPR
    • Misra, I.1    Shrivastava, A.2    Hebert, M.3
  • 40
    • 77956031473 scopus 로고    scopus 로고
    • A survey on transfer learning
    • S. J. Pan and Q. Yang. A survey on transfer learning. TKDE, 22(10):1345-1359, 2010
    • (2010) TKDE , vol.22 , Issue.10 , pp. 1345-1359
    • Pan, S.J.1    Yang, Q.2
  • 41
  • 42
    • 0003243224 scopus 로고    scopus 로고
    • Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods
    • J. C. Platt. Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. In Advances in large margin classifiers, 1999
    • (1999) Advances in Large Margin Classifiers
    • Platt, J.C.1
  • 43
    • 51949094374 scopus 로고    scopus 로고
    • Transfer learning for image classification with sparse prototype representations
    • A. Quattoni, M. Collins, and T. Darrell. Transfer learning for image classification with sparse prototype representations. In CVPR, 2008
    • (2008) CVPR
    • Quattoni, A.1    Collins, M.2    Darrell, T.3
  • 44
    • 84887356933 scopus 로고    scopus 로고
    • Attribute discovery via predictable discriminative binary codes
    • M. Rastegari, A. Farhadi, and D. Forsyth. Attribute discovery via predictable discriminative binary codes. In ECCV, 2012
    • (2012) ECCV
    • Rastegari, M.1    Farhadi, A.2    Forsyth, D.3
  • 45
    • 84897551647 scopus 로고    scopus 로고
    • Learning policies for contextual submodular prediction
    • S. Ross, J. Zhou, Y. Yue, D. Dey, and J. A. Bagnell. Learning policies for contextual submodular prediction. In ICML, 2013
    • (2013) ICML
    • Ross, S.1    Zhou, J.2    Yue, Y.3    Dey, D.4    Bagnell, J.A.5
  • 47
    • 36849095780 scopus 로고    scopus 로고
    • Restricted boltzmann machines for collaborative filtering
    • R. Salakhutdinov, A. Mnih, and G. Hinton. Restricted boltzmann machines for collaborative filtering. In ICML, 2007
    • (2007) ICML
    • Salakhutdinov, R.1    Mnih, A.2    Hinton, G.3
  • 49
    • 84900528296 scopus 로고    scopus 로고
    • Learning categories from few examples with multi model knowledge transfer
    • T. Tommasi, F. Orabona, and B. Caputo. Learning categories from few examples with multi model knowledge transfer. TPAMI, 36(5):928-941, 2014
    • (2014) TPAMI , vol.36 , Issue.5 , pp. 928-941
    • Tommasi, T.1    Orabona, F.2    Caputo, B.3
  • 50
    • 80052896768 scopus 로고    scopus 로고
    • Efficient object category recognition using classemes
    • L. Torresani, M. Szummer, and A. Fitzgibbon. Efficient object category recognition using classemes. In ECCV, 2010
    • (2010) ECCV
    • Torresani, L.1    Szummer, M.2    Fitzgibbon, A.3
  • 52
    • 84881160857 scopus 로고    scopus 로고
    • Selective search for object recognition
    • J. Uijlings, K. van de Sande, T. Gevers, and A. Smeulders. Selective search for object recognition. IJCV, 104(2):154-171, 2013
    • (2013) IJCV , vol.104 , Issue.2 , pp. 154-171
    • Uijlings, J.1    Sande De K.Van2    Gevers, T.3    Smeulders, A.4
  • 53
    • 84897584251 scopus 로고    scopus 로고
    • Nonnegative matrix factorization: A comprehensive review
    • Y.-X. Wang and Y.-J. Zhang. Nonnegative matrix factorization: A comprehensive review. TKDE, 25(6):1336-1353, 2013
    • (2013) TKDE , vol.25 , Issue.6 , pp. 1336-1353
    • Wang, Y.-X.1    Zhang, Y.-J.2
  • 54
    • 48349104603 scopus 로고    scopus 로고
    • Maximum margin matrix factorization for collaborative ranking
    • M. Weimer, A. Karatzoglou, Q. V. Le, and A. Smola. Maximum margin matrix factorization for collaborative ranking. In NIPS, 2007
    • (2007) NIPS
    • Weimer, M.1    Karatzoglou, A.2    Le, Q.V.3    Smola, A.4
  • 55
    • 48249137439 scopus 로고    scopus 로고
    • Collaborative filtering via ensembles of matrix factorizations
    • M. Wu. Collaborative filtering via ensembles of matrix factorizations. In Proceedings of KDD Cup and Workshop, 2007
    • (2007) Proceedings of KDD Cup and Workshop
    • Wu, M.1
  • 56
    • 84925433400 scopus 로고    scopus 로고
    • Efficient model evaluation with bilinear separation model
    • F. Xiao and M. Hebert. Efficient model evaluation with bilinear separation model. In WACV, 2015
    • (2015) WACV
    • Xiao, F.1    Hebert, M.2
  • 57
    • 84866665892 scopus 로고    scopus 로고
    • A codebook-free and annotation-free approach for fine-grained image categorization
    • B. Yao, G. Bradski, and L. Fei-Fei. A codebook-free and annotation-free approach for fine-grained image categorization. In CVPR, 2012
    • (2012) CVPR
    • Yao, B.1    Bradski, G.2    Fei-Fei, L.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.