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Volumn , Issue , 2014, Pages 504-511

Unrolling loopy top-down semantic feedback in convolutional deep networks

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE ENHANCEMENT; SEMANTIC WEB; SEMANTICS;

EID: 84908530334     PISSN: 21607508     EISSN: 21607516     Source Type: Conference Proceeding    
DOI: 10.1109/CVPRW.2014.80     Document Type: Conference Paper
Times cited : (27)

References (31)
  • 1
    • 84864073449 scopus 로고    scopus 로고
    • Greedy layer-wise training of deep networks
    • Y. Bengio, P. Lamblin, D. Popovici, and H. Larochelle. Greedy layer-wise training of deep networks. In NIPS, pages 153-160, 2006. 1, 2, 3
    • (2006) NIPS , pp. 153-160
    • Bengio, Y.1    Lamblin, P.2    Popovici, D.3    Larochelle, H.4
  • 2
    • 84855358881 scopus 로고    scopus 로고
    • Harmony potentials-Fusing global and local scale for semantic image segmentation
    • X. Boix, J. M. Gonfaus, J. van de Weijer, A. D. Bagdanov, J. S. Gual, and J. Gonzàlez. Harmony potentials-fusing global and local scale for semantic image segmentation. IJCV, 96(1):83-102, 2012. 2
    • (2012) IJCV , vol.96 , Issue.1 , pp. 83-102
    • Boix, X.1    Gonfaus, J.M.2    De W.J.Van3    Bagdanov, A.D.4    Gual, J.S.5    Gonzàlez, J.6
  • 3
    • 84894360206 scopus 로고    scopus 로고
    • Ecoc-drf: Discriminative random fields based on error-correcting output code
    • F. Ciompi, O. Pujol, and P. Radeva. Ecoc-drf: Discriminative random fields based on error-correcting output codes. Pattern Recognition, 47:2193-2204, 2014. 2
    • (2014) Pattern Recognition , vol.47 , pp. 2193-2204
    • Ciompi, F.1    Pujol, O.2    Radeva, P.3
  • 4
    • 80053446757 scopus 로고    scopus 로고
    • An analysis of singlelayer networks in unsupervised feature learning
    • A. Coates, H. Lee, and A. Y. Ng. An analysis of singlelayer networks in unsupervised feature learning. In AISTATS, pages 214-223, 2011. 2
    • (2011) AISTATS , pp. 214-223
    • Coates, A.1    Lee, H.2    Ng, A.Y.3
  • 5
    • 80053442434 scopus 로고    scopus 로고
    • The importance of encoding versus training with sparse coding and vector quantization
    • A. Coates and A. Ng. The importance of encoding versus training with sparse coding and vector quantization. In ICML, pages 921-928, 2011. 2
    • (2011) ICML , pp. 921-928
    • Coates, A.1    Ng, A.2
  • 8
    • 84876258641 scopus 로고    scopus 로고
    • Learning Hierarchical Features for Scene Labeling
    • C. Farabet, C. Couprie, L. Najman, and Y. LeCun. Learning hierarchical features for scene labeling. IEEE TPAMI, 35(8):1915-1929, 2013. 1, 2, 3, 5, 6, 7
    • (2013) IEEE TPAMI , vol.35 , Issue.8 , pp. 1915-1929
    • Farabet, C.1    Couprie, C.2    Najman, L.3    Lecun, Y.4
  • 9
    • 84908515201 scopus 로고    scopus 로고
    • Stacked sequential scale-space taylor context
    • C. Gatta and F. Ciompi. Stacked sequential scale-space taylor context. IEEE TPAMI, 2014. 2
    • (2014) IEEE TPAMI
    • Gatta, C.1    Ciompi, F.2
  • 11
    • 80052892113 scopus 로고    scopus 로고
    • A hierarchical conditional random field model for labeling and segmenting images of street scenes
    • IEEE
    • Q.-X. Huang, M. Han, B. Wu, and S. Ioffe. A hierarchical conditional random field model for labeling and segmenting images of street scenes. In CVPR, pages 1953-1960. IEEE, 2011. 2
    • (2011) CVPR , pp. 1953-1960
    • Huang, Q.-X.1    Han, M.2    Wu, B.3    Ioffe, S.4
  • 12
    • 70450182221 scopus 로고    scopus 로고
    • Efficient scale space auto-context for image segmentation and labeling
    • IEEE
    • J. Jiang and Z. Tu. Efficient scale space auto-context for image segmentation and labeling. In CVPR, pages 1810-1817. IEEE, 2009. 2
    • (2009) CVPR , pp. 1810-1817
    • Jiang, J.1    Tu, Z.2
  • 14
    • 61349174704 scopus 로고    scopus 로고
    • Robust higher order potentials for enforcing label consistency
    • P. Kohli, L. Ladicky, and P. H. S. Torr. Robust higher order potentials for enforcing label consistency. IJCV, 82(3):302-324, 2009. 2
    • (2009) IJCV , vol.82 , Issue.3 , pp. 302-324
    • Kohli, P.1    Ladicky, L.2    Torr, P.H.S.3
  • 15
    • 77953225585 scopus 로고    scopus 로고
    • Associative hierarchical crfs for object class image segmentation
    • IEEE
    • L. Ladicky, C. Russell, P. Kohli, and P. H. S. Torr. Associative hierarchical crfs for object class image segmentation. In ICCV, pages 739-746. IEEE, 2009. 2
    • (2009) ICCV , pp. 739-746
    • Ladicky, L.1    Russell, C.2    Kohli, P.3    Torr, P.H.S.4
  • 16
    • 78149343534 scopus 로고    scopus 로고
    • Graph cut based inference with co-occurrence statistics
    • Springer
    • L. Ladicky, C. Russell, P. Kohli, and P. H. S. Torr. Graph cut based inference with co-occurrence statistics. In ECCV (5), volume 6315 of LNCS, pages 239-253. Springer, 2010. 2
    • (2010) ECCV, LNCS , vol.6315 , Issue.5 , pp. 239-253
    • Ladicky, L.1    Russell, C.2    Kohli, P.3    Torr, P.H.S.4
  • 17
    • 85161980001 scopus 로고    scopus 로고
    • Sparse deep belief net model for visual area v2
    • H. Lee, C. Ekanadham, and A. Y. Ng. Sparse deep belief net model for visual area v2. In NIPS, pages 873-880, 2008. 2
    • (2008) NIPS , pp. 873-880
    • Lee, H.1    Ekanadham, C.2    Ng, A.Y.3
  • 18
    • 80054898486 scopus 로고    scopus 로고
    • Nonparametric scene parsing via label transfer
    • C. Liu, J. Yuen, and A. Torralba. Nonparametric scene parsing via label transfer. IEEE TPAMI, 33(12):2368-2382, 2011. 2, 5
    • (2011) IEEE TPAMI , vol.33 , Issue.12 , pp. 2368-2382
    • Liu, C.1    Yuen, J.2    Torralba, A.3
  • 19
    • 78149288414 scopus 로고    scopus 로고
    • Stacked hierarchical labeling
    • D. Munoz, J. A. D. Bagnell, and M. Hebert. Stacked hierarchical labeling. In ECCV, pages 57-70, 2010. 2
    • (2010) ECCV , pp. 57-70
    • Munoz, D.1    Bagnell, J.A.D.2    Hebert, M.3
  • 22
    • 0030779611 scopus 로고    scopus 로고
    • Sparse coding with an overcomplete basis set: A strategy employed by v1?
    • B. Olshausen and D. J. Field. Sparse coding with an overcomplete basis set: a strategy employed by v1? Vision Research, 37(23):3311-3325, 1997. 2
    • (1997) Vision Research , vol.37 , Issue.23 , pp. 3311-3325
    • Olshausen, B.1    Field, D.J.2
  • 23
    • 84925305292 scopus 로고    scopus 로고
    • Recurrent convolutional neural networks for scene labeling
    • P. Pinheiro and R. Collobert. Recurrent convolutional neural networks for scene labeling. JMLR, 1(32):82-90, 2014. 1, 2, 3, 4, 5, 6
    • (2014) JMLR , vol.1 , Issue.32 , pp. 82-90
    • Pinheiro, P.1    Collobert, R.2
  • 24
    • 84864069017 scopus 로고    scopus 로고
    • Efficient learning of sparse representations with an energy-based model
    • M. A. Ranzato, C. Poultney, S. Chopra, and Y. Lecun. Efficient learning of sparse representations with an energy-based model. In NIPS, pages 1137-1144, 2006. 2
    • (2006) NIPS , pp. 1137-1144
    • Ranzato, M.A.1    Poultney, C.2    Chopra, S.3    Lecun, Y.4
  • 25
    • 84908515199 scopus 로고    scopus 로고
    • No more metaparameter tuning in unsupervised sparse feature learning
    • A. Romero, P. Radeva, and C. Gatta. No more metaparameter tuning in unsupervised sparse feature learning. arXiv:1402. 5766, 2014. 2, 5
    • (2014) Arxiv:1402. 5766
    • Romero, A.1    Radeva, P.2    Gatta, C.3
  • 26
    • 84866707104 scopus 로고    scopus 로고
    • Structured local predictors for image labelling
    • IEEE
    • S. Rota Bulò, P. Kontschieder, M. Pelillo, and H. Bischof. Structured local predictors for image labelling. In CVPR, pages 3530-3537. IEEE, 2012. 2
    • (2012) CVPR , pp. 3530-3537
    • Rota Bulò, S.1    Kontschieder, P.2    Pelillo, M.3    Bischof, H.4
  • 27
    • 84906907367 scopus 로고    scopus 로고
    • Pedestrian detection with unsupervised multi-stage feature learning
    • P. Sermanet, K. Kavukcuoglu, S. Chintala, and Y. LeCun. Pedestrian detection with unsupervised multi-stage feature learning. In CVPR. 3
    • CVPR
    • Sermanet, P.1    Kavukcuoglu, K.2    Chintala, S.3    Lecun, Y.4
  • 28
    • 84887364799 scopus 로고    scopus 로고
    • Nonparametric scene parsing with adaptive feature relevance and semantic context
    • IEEE, 1, 2, 3, 5, 6
    • G. Singh and J. Kosecka. Nonparametric scene parsing with adaptive feature relevance and semantic context. In CVPR, pages 3151-3157. IEEE, 2013. 1, 2, 3, 5, 6
    • (2013) CVPR , pp. 3151-3157
    • Singh, G.1    Kosecka, J.2
  • 29
    • 84873190838 scopus 로고    scopus 로고
    • Superparsing-Scalable nonparametric image parsing with superpixels
    • J. Tighe and S. Lazebnik. Superparsing-scalable nonparametric image parsing with superpixels. IJCV, 101(2):329-349, 2013. 2
    • (2013) IJCV , vol.101 , Issue.2 , pp. 329-349
    • Tighe, J.1    Lazebnik, S.2
  • 30
    • 77956051102 scopus 로고    scopus 로고
    • Auto-context and its application to highlevel vision tasks and 3d brain image segmentation
    • Z. Tu and X. Bai. Auto-context and its application to highlevel vision tasks and 3d brain image segmentation. IEEE TPAMI, 32(10):1744-1757, 2010. 2
    • (2010) IEEE TPAMI , vol.32 , Issue.10 , pp. 1744-1757
    • Tu, Z.1    Bai, X.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.