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Volumn 2016-December, Issue , 2016, Pages 4651-4659

Image captioning with semantic attention

Author keywords

[No Author keywords available]

Indexed keywords

NATURAL LANGUAGE PROCESSING SYSTEMS; PATTERN RECOGNITION; RECURRENT NEURAL NETWORKS; SEMANTICS;

EID: 84986317307     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.503     Document Type: Conference Paper
Times cited : (1902)

References (38)
  • 1
    • 85083951423 scopus 로고    scopus 로고
    • Multiple object recognition with visual attention
    • J. Ba, V. Mnih, and K. Kavukcuoglu. Multiple object recognition with visual attention. ICLR, 2015.
    • (2015) ICLR
    • Ba, J.1    Mnih, V.2    Kavukcuoglu, K.3
  • 2
    • 84965166940 scopus 로고    scopus 로고
    • Neural machine translation by jointly learning to align and translate
    • D. Bahdanau, K. Cho, and Y. Bengio. Neural machine translation by jointly learning to align and translate. ICLR, 2014.
    • (2014) ICLR
    • Bahdanau, D.1    Cho, K.2    Bengio, Y.3
  • 4
    • 84957029470 scopus 로고    scopus 로고
    • Mind's eye: A recurrent visual representation for image caption generation
    • X. Chen and C. L. Zitnick. Mind's eye: A recurrent visual representation for image caption generation. In CVPR, pages 2422-2431, 2015.
    • (2015) CVPR , pp. 2422-2431
    • Chen, X.1    Zitnick, C.L.2
  • 6
    • 84867478719 scopus 로고    scopus 로고
    • Learning where to attend with deep architectures for image tracking
    • M. Denil, L. Bazzani, H. Larochelle, and N. de Freitas. Learning where to attend with deep architectures for image tracking. Neural computation, 24(8):2151-2184, 2012.
    • (2012) Neural Computation , vol.24 , Issue.8 , pp. 2151-2184
    • Denil, M.1    Bazzani, L.2    Larochelle, H.3    De Freitas, N.4
  • 9
    • 84906929591 scopus 로고    scopus 로고
    • Image description using visual dependency representations
    • D. Elliott and F. Keller. Image description using visual dependency representations. In EMNLP, pages 1292-1302, 2013.
    • (2013) EMNLP , pp. 1292-1302
    • Elliott, D.1    Keller, F.2
  • 10
    • 84959190514 scopus 로고    scopus 로고
    • On the relationship between visual attributes and convolutional networks
    • V. Escorcia, J. C. Niebles, and B. Ghanem. On the relationship between visual attributes and convolutional networks. In CVPR, pages 1256-1264, 2015.
    • (2015) CVPR , pp. 1256-1264
    • Escorcia, V.1    Niebles, J.C.2    Ghanem, B.3
  • 13
    • 85083950293 scopus 로고    scopus 로고
    • Deep convolutional ranking for multilabel image annotation
    • Y. Gong, Y. Jia, T. Leung, A. Toshev, and S. Ioffe. Deep convolutional ranking for multilabel image annotation. ICLR, 2014.
    • (2014) ICLR
    • Gong, Y.1    Jia, Y.2    Leung, T.3    Toshev, A.4    Ioffe, S.5
  • 14
    • 84906484732 scopus 로고    scopus 로고
    • Improving image-sentence embeddings using large weakly annotated photo collections
    • Springer
    • Y. Gong, L. Wang, M. Hodosh, J. Hockenmaier, and S. Lazebnik. Improving image-sentence embeddings using large weakly annotated photo collections. In ECCV, pages 529-545. Springer, 2014.
    • (2014) ECCV , pp. 529-545
    • Gong, Y.1    Wang, L.2    Hodosh, M.3    Hockenmaier, J.4    Lazebnik, S.5
  • 16
    • 84946734827 scopus 로고    scopus 로고
    • Deep visual-semantic alignments for generating image descriptions
    • June
    • A. Karpathy and L. Fei-Fei. Deep visual-semantic alignments for generating image descriptions. In CVPR, June 2015.
    • (2015) CVPR
    • Karpathy, A.1    Fei-Fei, L.2
  • 17
    • 0003153058 scopus 로고
    • Shifts in selective visual attention: Towards the underlying neural circuitry
    • Springer
    • C. Koch and S. Ullman. Shifts in selective visual attention: towards the underlying neural circuitry. In Matters of intelligence, pages 115-141. Springer, 1987.
    • (1987) Matters of Intelligence , pp. 115-141
    • Koch, C.1    Ullman, S.2
  • 18
    • 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, pages 1097-1105, 2012.
    • (2012) NIPS , pp. 1097-1105
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 20
    • 84878189119 scopus 로고    scopus 로고
    • Collective generation of natural image descriptions
    • P. Kuznetsova, V. Ordonez, A. C. Berg, T. L. Berg, and Y. Choi. Collective generation of natural image descriptions. In ACL, pages 359-368, 2012.
    • (2012) ACL , pp. 359-368
    • Kuznetsova, P.1    Ordonez, V.2    Berg, A.C.3    Berg, T.L.4    Choi, Y.5
  • 21
    • 85162061663 scopus 로고    scopus 로고
    • Learning to combine foveal glimpses with a third-order boltzmann machine
    • H. Larochelle and G. E. Hinton. Learning to combine foveal glimpses with a third-order boltzmann machine. In NIPS, pages 1243-1251, 2010.
    • (2010) NIPS , pp. 1243-1251
    • Larochelle, H.1    Hinton, G.E.2
  • 22
    • 85083952381 scopus 로고    scopus 로고
    • Simple image description generator via a linear phrase-based approach
    • R. Lebret, P. O. Pinheiro, and R. Collobert. Simple image description generator via a linear phrase-based approach. ICLR, 2015.
    • (2015) ICLR
    • Lebret, R.1    Pinheiro, P.O.2    Collobert, R.3
  • 23
    • 84862279067 scopus 로고    scopus 로고
    • Composing simple image descriptions using web-scale ngrams
    • S. Li, G. Kulkarni, T. L. Berg, A. C. Berg, and Y. Choi. Composing simple image descriptions using web-scale ngrams. In CoNLL, pages 220-228, 2011.
    • (2011) CoNLL , pp. 220-228
    • Li, S.1    Kulkarni, G.2    Berg, T.L.3    Berg, A.C.4    Choi, Y.5
  • 24
    • 84959205572 scopus 로고    scopus 로고
    • Fully convolutional networks for semantic segmentation
    • June
    • J. Long, E. Shelhamer, and T. Darrell. Fully convolutional networks for semantic segmentation. In CVPR, June 2015.
    • (2015) CVPR
    • Long, J.1    Shelhamer, E.2    Darrell, T.3
  • 25
    • 84973863256 scopus 로고    scopus 로고
    • Learning like a child: Fast novel visual concept learning from sentence descriptions of images
    • J. Mao, W. Xu, Y. Yang, J. Wang, Z. Huang, and A. Yuille. Learning like a child: Fast novel visual concept learning from sentence descriptions of images. In ICCV, 2015.
    • (2015) ICCV
    • Mao, J.1    Xu, W.2    Yang, Y.3    Wang, J.4    Huang, Z.5    Yuille, A.6
  • 27
    • 84898956512 scopus 로고    scopus 로고
    • Distributed representations of words and phrases and their compositionality
    • T. Mikolov, I. Sutskever, K. Chen, G. S. Corrado, and J. Dean. Distributed representations of words and phrases and their compositionality. In NIPS, pages 3111-3119, 2013.
    • (2013) NIPS , pp. 3111-3119
    • Mikolov, T.1    Sutskever, I.2    Chen, K.3    Corrado, G.S.4    Dean, J.5
  • 28
    • 84937959846 scopus 로고    scopus 로고
    • Recurrent models of visual attention
    • V. Mnih, N. Heess, A. Graves, et al. Recurrent models of visual attention. In NIPS, pages 2204-2212, 2014.
    • (2014) NIPS , pp. 2204-2212
    • Mnih, V.1    Heess, N.2    Graves, A.3
  • 29
    • 84961289992 scopus 로고    scopus 로고
    • Glove: Global vectors for word representation
    • J. Pennington, R. Socher, and C. D. Manning. Glove: Global vectors for word representation. EMNLP, 12:1532-1543, 2014.
    • (2014) EMNLP , vol.12 , pp. 1532-1543
    • Pennington, J.1    Socher, R.2    Manning, C.D.3
  • 31
    • 84928547704 scopus 로고    scopus 로고
    • Sequence to sequence learning with neural networks
    • I. Sutskever, O. Vinyals, and Q. V. Le. Sequence to sequence learning with neural networks. In NIPS, pages 3104-3112, 2014.
    • (2014) NIPS , pp. 3104-3112
    • Sutskever, I.1    Vinyals, O.2    Le, Q.V.3
  • 33
    • 84937843152 scopus 로고    scopus 로고
    • Learning generative models with visual attention
    • Y. Tang, N. Srivastava, and R. R. Salakhutdinov. Learning generative models with visual attention. In NIPS, pages 1808-1816, 2014.
    • (2014) NIPS , pp. 1808-1816
    • Tang, Y.1    Srivastava, N.2    Salakhutdinov, R.R.3
  • 35
    • 84946747440 scopus 로고    scopus 로고
    • Show and tell: A neural image caption generator
    • O. Vinyals, A. Toshev, S. Bengio, and D. Erhan. Show and tell: A neural image caption generator. In CVPR, pages 3156-3164, 2015.
    • (2015) CVPR , pp. 3156-3164
    • Vinyals, O.1    Toshev, A.2    Bengio, S.3    Erhan, D.4
  • 36
    • 84986301177 scopus 로고    scopus 로고
    • What Value Do Explicit High-Level Concepts Have in Vision to Language Problems?
    • Q. Wu, C. Shen, A. van den Hengel, L. Liu, and A. Dick. What Value Do Explicit High-Level Concepts Have in Vision to Language Problems? In CVPR, 2016.
    • (2016) CVPR
    • Wu, Q.1    Shen, C.2    Hengel Den A.Van3    Liu, L.4    Dick, A.5
  • 38
    • 84959187860 scopus 로고    scopus 로고
    • Conceptlearner: Discovering visual concepts from weakly labeled image collections
    • June
    • B. Zhou, V. Jagadeesh, and R. Piramuthu. Conceptlearner: Discovering visual concepts from weakly labeled image collections. In CVPR, June 2015.
    • (2015) CVPR
    • Zhou, B.1    Jagadeesh, V.2    Piramuthu, R.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.