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Volumn 100, Issue 3, 2012, Pages 275-293

Weakly supervised localization and learning with generic knowledge

Author keywords

Conditional random fields; Object detection; Transfer learning; Weakly supervised learning

Indexed keywords

APPEARANCE MODELS; CONDITIONAL RANDOM FIELD; DATA SETS; OBJECT CLASS; OBJECT DETECTION; OBJECT DETECTORS; OBJECT LOCATION; SUPERVISED LOCALIZATION; TRAINING IMAGE; TRANSFER LEARNING; WEAKLY SUPERVISED LEARNING;

EID: 84867062047     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-012-0538-3     Document Type: Article
Times cited : (320)

References (65)
  • 1
    • 80052912891 scopus 로고    scopus 로고
    • ClassCut for unsupervised class segmentation
    • Alexe, B., Deselaers, T., & Ferrari, V. (2010a). ClassCut for unsupervised class segmentation. In ECCV.
    • (2010) ECCV
    • Alexe, B.1    Deselaers, T.2    Ferrari, V.3
  • 4
    • 85141266799 scopus 로고    scopus 로고
    • Support vector machines for multiple-instance learning
    • Andrews, S., Tsochantaridis, I., & Hofmann, T. (2002). Support vector machines for multiple-instance learning. In NIPS.
    • (2002) NIPS
    • Andrews, S.1    Tsochantaridis, I.2    Hofmann, T.3
  • 5
    • 34948875827 scopus 로고    scopus 로고
    • Unsupervised segmentation of objects using efficient learning
    • Arora, H., Loeff, N., Forsyth, D., & Ahuja, N. (2007). Unsupervised segmentation of objects using efficient learning. In CVPR.
    • (2007) CVPR
    • Arora, H.1    Loeff, N.2    Forsyth, D.3    Ahuja, N.4
  • 6
    • 77953185204 scopus 로고    scopus 로고
    • Similarity metrics for categorization: From monolithic to category specific
    • Babenko, B., Branson, S., & Belongie, S. (2009). Similarity metrics for categorization: From monolithic to category specific. In ICCV.
    • (2009) ICCV
    • Babenko, B.1    Branson, S.2    Belongie, S.3
  • 9
    • 85161984064 scopus 로고    scopus 로고
    • Simultaneous object detection and ranking with weak supervision
    • Blaschko, B., Vedaldi, A., & Zisserman, A. (2010). Simultaneous object detection and ranking with weak supervision. In NIPS.
    • (2010) NIPS
    • Blaschko, B.1    Vedaldi, A.2    Zisserman, A.3
  • 11
    • 50649087214 scopus 로고    scopus 로고
    • Spatially coherent latent topic model for concurrent segmentation and classification of objects and scene
    • Cao, L., & Li, F. F. (2007). Spatially coherent latent topic model for concurrent segmentation and classification of objects and scene. In ICCV.
    • (2007) ICCV
    • Cao, L.1    Li, F.F.2
  • 12
    • 77956008665 scopus 로고    scopus 로고
    • Constrained parametric min cuts for automatic object segmentation
    • Carreira, J., Li, F., & Sminchisescu, C. (2010). Constrained parametric min cuts for automatic object segmentation. In CVPR.
    • (2010) CVPR
    • Carreira, J.1    Li, F.2    Sminchisescu, C.3
  • 14
    • 34948855941 scopus 로고    scopus 로고
    • An exemplar model for learning object classes
    • Chum, O., & Zisserman, A. (2007). An exemplar model for learning object classes. In CVPR.
    • (2007) CVPR
    • Chum, O.1    Zisserman, A.2
  • 15
    • 34948861144 scopus 로고    scopus 로고
    • Weakly supervised learning of part-based spatial models for visual object recognition
    • Crandall, D. J., & Huttenlocher, D. (2006). Weakly supervised learning of part-based spatial models for visual object recognition. In ECCV.
    • (2006) ECCV
    • Crandall, D.J.1    Huttenlocher, D.2
  • 16
    • 33645146449 scopus 로고    scopus 로고
    • Histogram of Oriented Gradients for human detection
    • Dalal, N., & Triggs, B. (2005). Histogram of Oriented Gradients for human detection. In CVPR.
    • (2005) CVPR
    • Dalal, N.1    Triggs, B.2
  • 17
    • 77956555219 scopus 로고    scopus 로고
    • A conditional random field for multiple-instance learning
    • Deselaers, T., & Ferrari, V. (2010). A conditional random field for multiple-instance learning. In ICML.
    • (2010) ICML
    • Deselaers, T.1    Ferrari, V.2
  • 18
    • 79959728283 scopus 로고    scopus 로고
    • Localizing objects while learning their appearance
    • Deselaers, T., Alexe, B., & Ferrari, V. (2010). Localizing objects while learning their appearance. In ECCV.
    • (2010) ECCV
    • Deselaers, T.1    Alexe, B.2    Ferrari, V.3
  • 20
    • 79851509694 scopus 로고    scopus 로고
    • Category independent object proposals
    • Endres, I., & Hoiem, D. (2010). Category independent object proposals. In ECCV.
    • (2010) ECCV
    • Endres, I.1    Hoiem, D.2
  • 24
    • 0344983284 scopus 로고    scopus 로고
    • A bayesian approach to unsupervised one-shot learning of object categories
    • Fei-Fei, L., Fergus, R., & Perona, P. (2003). A bayesian approach to unsupervised one-shot learning of object categories. In ICCV (pp. 1134-1141).
    • (2003) ICCV , pp. 1134-1141
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 25
    • 84932617705 scopus 로고    scopus 로고
    • Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories
    • Fei-Fei, L., Fergus, R., & Perona, P. (2004). Learning generative visual models from few training examples: an incremental Bayesian approach tested on 101 object categories. In CVPR workshop of generative model based vision.
    • (2004) CVPR Workshop of Generative Model Based Vision
    • Fei-Fei, L.1    Fergus, R.2    Perona, P.3
  • 27
    • 0041940256 scopus 로고    scopus 로고
    • Object class recognition by unsupervised scale-invariant learning
    • Fergus, R., Perona, P., & Zisserman, A. (2003). Object class recognition by unsupervised scale-invariant learning. In CVPR.
    • (2003) CVPR
    • Fergus, R.1    Perona, P.2    Zisserman, A.3
  • 28
    • 56449113929 scopus 로고    scopus 로고
    • Training structural svms when exact inference is intractable
    • Finley, T., & Joachims, T. (2008). Training structural svms when exact inference is intractable. In ICML.
    • (2008) ICML
    • Finley, T.1    Joachims, T.2
  • 29
    • 34948836238 scopus 로고    scopus 로고
    • Towards unsupervised discovery of visual categories
    • Fritz, M., & Schiele, B. (2006). Towards unsupervised discovery of visual categories. In DAGM.
    • (2006) DAGM
    • Fritz, M.1    Schiele, B.2
  • 30
    • 50649117726 scopus 로고    scopus 로고
    • Learning globallyconsistent local distance functions for shape-based image retrieval and classification
    • Frome, A., Singer, Y., Sha, F., & Malik, J. (2007). Learning globallyconsistent local distance functions for shape-based image retrieval and classification. In ICCV.
    • (2007) ICCV
    • Frome, A.1    Singer, Y.2    Sha, F.3    Malik, J.4
  • 32
    • 77955997018 scopus 로고    scopus 로고
    • Weakly supervised object localization with stable segmentations
    • Galleguillos, C., Babenko, B., Rabinovich, A., & Belongie, S. (2008). Weakly supervised object localization with stable segmentations. In ECCV.
    • (2008) ECCV
    • Galleguillos, C.1    Babenko, B.2    Rabinovich, A.3    Belongie, S.4
  • 33
    • 33845575890 scopus 로고    scopus 로고
    • Unsupervised learning of categories from sets of partially matching image features
    • Grauman, K., & Darrell, T. (2006). Unsupervised learning of categories from sets of partially matching image features. In CVPR.
    • (2006) CVPR
    • Grauman, K.1    Darrell, T.2
  • 34
    • 84856671399 scopus 로고    scopus 로고
    • Unsupervised detection of regions of interest using iterative link analysis
    • Kim, G., & Torralba, A. (2009). Unsupervised detection of regions of interest using iterative link analysis. In NIPS.
    • (2009) NIPS
    • Kim, G.1    Torralba, A.2
  • 35
    • 33750129298 scopus 로고    scopus 로고
    • Convergent tree-reweighted message passing for energy minimization
    • DOI 10.1109/TPAMI.2006.200
    • Kolmogorov, V. (2006a). Convergent tree-reweighted message passing for energy minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10), 1568-1583. (Pubitemid 46405078)
    • (2006) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.28 , Issue.10 , pp. 1568-1583
    • Kolmogorov, V.1
  • 36
    • 33750129298 scopus 로고    scopus 로고
    • Convergent tree-reweighted message passing for energy minimization
    • DOI 10.1109/TPAMI.2006.200
    • Kolmogorov, V. (2006b). Convergent tree-reweighted message passing for energy minimization. IEEE Transactions on Pattern Analysis and Machine Intelligence, 28(10), 1568-1583. (Pubitemid 46405078)
    • (2006) IEEE Transactions on Pattern Analysis and Machine Intelligence , vol.28 , Issue.10 , pp. 1568-1583
    • Kolmogorov, V.1
  • 37
    • 70450172710 scopus 로고    scopus 로고
    • Learning to detect unseen object classes by between-class attribute transfer
    • Lampert, C., Nickisch, H., & Harmeling, S. (2009a). Learning to detect unseen object classes by between-class attribute transfer. In CVPR.
    • (2009) CVPR
    • Lampert, C.1    Nickisch, H.2    Harmeling, S.3
  • 40
    • 70450169648 scopus 로고    scopus 로고
    • Shape discovery from unlabeled image collections
    • Lee, Y., & Grauman, K. (2009a). Shape discovery from unlabeled image collections. In CVPR.
    • (2009) CVPR
    • Lee, Y.1    Grauman, K.2
  • 41
    • 68849114784 scopus 로고    scopus 로고
    • Foreground focus: Unsupervised learning from partially matching images
    • Lee, Y. J., & Grauman, K. (2009b). Foreground focus: unsupervised learning from partially matching images. International Journal of Computer Vision, 85, 143-166.
    • (2009) International Journal of Computer Vision , vol.85 , pp. 143-166
    • Lee, Y.J.1    Grauman, K.2
  • 42
    • 51949096556 scopus 로고    scopus 로고
    • Recognition by association via learning per-exemplar distances
    • Malisiewicz, T., & Efros, A. A. (2008). Recognition by association via learning per-exemplar distances. In CVPR.
    • (2008) CVPR
    • Malisiewicz, T.1    Efros, A.A.2
  • 43
    • 77953182042 scopus 로고    scopus 로고
    • Weakly supervised discriminative localization and classification: A joint learning process
    • Nguyen, M., Torresani, L., de la Torre, F., & Rother, C. (2009).Weakly supervised discriminative localization and classification: a joint learning process. In ICCV.
    • (2009) ICCV
    • Nguyen, M.1    Torresani, L.2    De La Torre, F.3    Rother, C.4
  • 44
    • 34948866276 scopus 로고    scopus 로고
    • Learning visual similarity measures for comparing never seen objects
    • Nowak, E., & Jurie, F. (2007). Learning visual similarity measures for comparing never seen objects. In CVPR.
    • (2007) CVPR
    • Nowak, E.1    Jurie, F.2
  • 45
    • 0035328421 scopus 로고    scopus 로고
    • Modeling the shape of the scene: A holistic representation of the spatial envelope
    • DOI 10.1023/A:1011139631724
    • Oliva, A., & Torralba, A. (2001). Modeling the shape of the scene: a holistic representation of the spatial envelope. International Journal of Computer Vision 42(3) 145-175. (Pubitemid 32680801)
    • (2001) International Journal of Computer Vision , vol.42 , Issue.3 , pp. 145-175
    • Oliva, A.1    Torralba, A.2
  • 46
    • 84860632234 scopus 로고    scopus 로고
    • From a set of shapes to object discovery
    • Payet, N., & Todorovic, S. (2010). From a set of shapes to object discovery. In ECCV.
    • (2010) ECCV
    • Payet, N.1    Todorovic, S.2
  • 47
    • 51949094374 scopus 로고    scopus 로고
    • Transfer learning for image classification with sparse prototype representations
    • Quattoni, A., Collins, M., & Darrell, T. (2008). Transfer learning for image classification with sparse prototype representations. In CVPR.
    • (2008) CVPR
    • Quattoni, A.1    Collins, M.2    Darrell, T.3
  • 48
    • 51949106645 scopus 로고    scopus 로고
    • Self-taught learning: Transfer learning from unlabeled data
    • Raina, R., Battle, A., Lee, H., Packer, B., & Ng, A. (2007). Self-taught learning: transfer learning from unlabeled data. In ICML.
    • (2007) ICML
    • Raina, R.1    Battle, A.2    Lee, H.3    Packer, B.4    Ng, A.5
  • 49
    • 85134634152 scopus 로고    scopus 로고
    • Learning to parse images of articulated bodies
    • Ramanan, D. (2006). Learning to parse images of articulated bodies. In NIPS.
    • (2006) NIPS
    • Ramanan, D.1
  • 50
    • 77955989949 scopus 로고    scopus 로고
    • What helps where-and why? semantic relatedness for knowledge transfer
    • Rohrbach, M., Stark, M., Szarvas, G., Gurevych, I., & Schiele, B. (2010). What helps where-and why? semantic relatedness for knowledge transfer. In CVPR.
    • (2010) CVPR
    • Rohrbach, M.1    Stark, M.2    Szarvas, G.3    Gurevych, I.4    Schiele, B.5
  • 51
    • 12844262766 scopus 로고    scopus 로고
    • Grabcut: Interactive foreground extraction using iterated graph cuts
    • Rother, C., Kolmogorov, V., & Blake, A. (2004). Grabcut: interactive foreground extraction using iterated graph cuts. Computer Graphics, 23(3), 309-314.
    • (2004) Computer Graphics , vol.23 , Issue.3 , pp. 309-314
    • Rother, C.1    Kolmogorov, V.2    Blake, A.3
  • 52
    • 39749186006 scopus 로고    scopus 로고
    • LabelMe: A database and webbased tool for image annotation
    • Russel, B. C., & Torralba, A. (2008). LabelMe: a database and webbased tool for image annotation. International Journal of Computer Vision, 77(1-3), 157-173.
    • (2008) International Journal of Computer Vision , vol.77 , Issue.1-3 , pp. 157-173
    • Russel, B.C.1    Torralba, A.2
  • 53
    • 33845596932 scopus 로고    scopus 로고
    • Using multiple segmentations to discover objects and their extent in image collections
    • Russell, B. C., Efros, A. A., Sivic, J., Freeman, W. T., & Zisserman, A. (2006). Using multiple segmentations to discover objects and their extent in image collections. In CVPR.
    • (2006) CVPR
    • Russell, B.C.1    Efros, A.A.2    Sivic, J.3    Freeman, W.T.4    Zisserman, A.5
  • 54
    • 77953222843 scopus 로고    scopus 로고
    • A shape-based object class model for knowledge transfer
    • Stark, M., Goesele, M., & Schiele, B. (2009). A shape-based object class model for knowledge transfer. In ICCV.
    • (2009) ICCV
    • Stark, M.1    Goesele, M.2    Schiele, B.3
  • 55
    • 70450204874 scopus 로고    scopus 로고
    • Learning CRFs using graph cuts
    • Szummer, M., Kohli, P., & Hoiem, D. (2008). Learning CRFs using graph cuts. In ECCV.
    • (2008) ECCV
    • Szummer, M.1    Kohli, P.2    Hoiem, D.3
  • 56
    • 0041494227 scopus 로고    scopus 로고
    • Is learning the n-th thing any easier than learning the first?
    • Thrun, S. (1996). Is learning the n-th thing any easier than learning the first? In NIPS.
    • (1996) NIPS
    • Thrun, S.1
  • 57
    • 33845579921 scopus 로고    scopus 로고
    • Extracting subimages of an unknown category from a set of images
    • Todorovic, S., & Ahuja, N. (2006). Extracting subimages of an unknown category from a set of images. In CVPR.
    • (2006) CVPR
    • Todorovic, S.1    Ahuja, N.2
  • 58
    • 84898876496 scopus 로고    scopus 로고
    • The more you know, the less you learn: From knowledge transfer to one-shot learning of object categories
    • Tommasi, T., & Caputo, B. (2009). The more you know, the less you learn: from knowledge transfer to one-shot learning of object categories. In BMVC.
    • (2009) BMVC
    • Tommasi, T.1    Caputo, B.2
  • 59
    • 77956005674 scopus 로고    scopus 로고
    • Safety in numbers: Learning categories from few examples with multi model knowledge transfer
    • Tommasi, T., Orabona, F., & Caputo, B. (2010). Safety in numbers: learning categories from few examples with multi model knowledge transfer. In CVPR.
    • (2010) CVPR
    • Tommasi, T.1    Orabona, F.2    Caputo, B.3
  • 60
    • 80052896768 scopus 로고    scopus 로고
    • Efficient object category recognition using classemes
    • Torresani, L., Szummer, M., & Fitzgibbon, A. (2010). Efficient object category recognition using classemes. In ECCV.
    • (2010) ECCV
    • Torresani, L.1    Szummer, M.2    Fitzgibbon, A.3
  • 62
    • 84864049528 scopus 로고    scopus 로고
    • Multiple instance boosting for object detection
    • Viola, P. A., Platt, J., & Zhang, C. (2005). Multiple instance boosting for object detection. In NIPS.
    • (2005) NIPS
    • Viola, P.A.1    Platt, J.2    Zhang, C.3
  • 63
    • 33749257955 scopus 로고    scopus 로고
    • Distance metric learning for large margin nearest neighbor classification
    • Weinberger, K. Q., Blitzer, J., & Saul, L. K. (2005). Distance metric learning for large margin nearest neighbor classification. In NIPS.
    • (2005) NIPS
    • Weinberger, K.Q.1    Blitzer, J.2    Saul, L.K.3
  • 64
    • 33745948591 scopus 로고    scopus 로고
    • LOCUS: Learning object classes with unsupervised segmentation
    • Winn, J., & Jojic, N. (2005a). LOCUS: learning object classes with unsupervised segmentation. In ICCV.
    • (2005) ICCV
    • Winn, J.1    Jojic, N.2
  • 65
    • 33846580425 scopus 로고    scopus 로고
    • Local features and kernels for classification of texture and object categories: A comprehensive study
    • DOI 10.1007/s11263-006-9794-4
    • Zhang, J., Marszalek, M., Lazebnik, S., & Schmid, C. (2007). Local features and kernels for classification of texture and object categories: a comprehensive study. International Journal of Computer Vision, 73(2), 213-238 (Pubitemid 46181625)
    • (2007) International Journal of Computer Vision , vol.73 , Issue.2 , pp. 213-238
    • Zhang, J.1    Marszalek, M.2    Lazebnik, S.3    Schmid, C.4


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