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Volumn 2017-January, Issue , 2017, Pages 6412-6421

Gaze embeddings for zero-shot image classification

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; IMAGE CLASSIFICATION;

EID: 85041917180     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.679     Document Type: Conference Paper
Times cited : (103)

References (52)
  • 3
    • 84959243017 scopus 로고    scopus 로고
    • Evaluation of output embeddings for fine-grained image classification
    • Z. Akata, S. Reed, D. Walter, H. Lee, and B. Schiele. Evaluation of output embeddings for fine-grained image classification. In CVPR, 2015.
    • (2015) CVPR
    • Akata, Z.1    Reed, S.2    Walter, D.3    Lee, H.4    Schiele, B.5
  • 4
    • 84887325349 scopus 로고    scopus 로고
    • Fine-grained crowdsourc-ing for fine-grained recognition
    • J. Deng, J. Krause, and L. Fei-Fei. Fine-grained crowdsourc-ing for fine-grained recognition. In CVPR, 2013.
    • (2013) CVPR
    • Deng, J.1    Krause, J.2    Fei-Fei, L.3
  • 6
    • 70450219358 scopus 로고    scopus 로고
    • Learning visual attributes
    • V. Ferrari and A. Zisserman. Learning visual attributes. In NIPS, 2007.
    • (2007) NIPS
    • Ferrari, V.1    Zisserman, A.2
  • 7
    • 80052885911 scopus 로고    scopus 로고
    • Comparing data-dependent and data-independent embeddings for classification and ranking of internet images
    • Y. Gong and S. Lazebnik. Comparing data-dependent and data-independent embeddings for classification and ranking of internet images. In CVPR, 2011.
    • (2011) CVPR
    • Gong, Y.1    Lazebnik, S.2
  • 10
    • 0029353751 scopus 로고
    • Pupil dilation as a measure of processing load in simultaneous interpretation and other language tasks
    • J. Hyönä, J. Tommola, and A.-M. Alaja. Pupil dilation as a measure of processing load in simultaneous interpretation and other language tasks. The Quarterly Journal of Experimental Psychology, 48(3):598-612, 1995.
    • (1995) The Quarterly Journal of Experimental Psychology , vol.48 , Issue.3 , pp. 598-612
    • Hyönä, J.1    Tommola, J.2    Alaja, A.-M.3
  • 11
    • 85044499492 scopus 로고    scopus 로고
    • Leveraging the wisdom of the crowd for fine-grained recognition
    • press
    • M. S. L. F.-F. Jia Deng, Jonathan Krause. Leveraging the wisdom of the crowd for fine-grained recognition. TPAMI, in press.
    • TPAMI
    • Jia Deng, L.F.-F.1    Krause, J.2
  • 12
    • 77953205576 scopus 로고    scopus 로고
    • Learning to predict where humans look
    • T. Judd, K. Ehinger, F. Durand, and A. Torralba. Learning to predict where humans look. In ICCV, pages 2106-2113, 2009.
    • (2009) ICCV , pp. 2106-2113
    • Judd, T.1    Ehinger, K.2    Durand, F.3    Torralba, A.4
  • 14
    • 84959236867 scopus 로고    scopus 로고
    • Eye tracking assisted extraction of attentionally important objects from videos
    • S. Karthikeyan, T. Ngo, M. Eckstein, and B. Manjunath. Eye tracking assisted extraction of attentionally important objects from videos. In Proc. CVPR, pages 3241-3250, 2015.
    • (2015) Proc. CVPR , pp. 3241-3250
    • Karthikeyan, S.1    Ngo, T.2    Eckstein, M.3    Manjunath, B.4
  • 15
    • 77953185711 scopus 로고    scopus 로고
    • Attribute and simile classifiers for face verification
    • N. Kumar, A. C. Berg, P. N. Belhumeur, and S. K. Nayar. Attribute and simile classifiers for face verification. In ICCV, 2009.
    • (2009) ICCV
    • Kumar, N.1    Berg, A.C.2    Belhumeur, P.N.3    Nayar, S.K.4
  • 16
    • 84925402963 scopus 로고    scopus 로고
    • Attribute-based classification for zero-shot visual object categorization
    • C. Lampert, H. Nickisch, and S. Harmeling. Attribute-based classification for zero-shot visual object categorization. In TPAMI, 2013.
    • (2013) TPAMI
    • Lampert, C.1    Nickisch, H.2    Harmeling, S.3
  • 17
    • 70449565636 scopus 로고    scopus 로고
    • A dataset and evaluation methodology for visual saliency in video
    • J. Li, Y. Tian, T. Huang, and W. Gao. A dataset and evaluation methodology for visual saliency in video. In ICME, pages 442-445, 2009.
    • (2009) ICME , pp. 442-445
    • Li, J.1    Tian, Y.2    Huang, T.3    Gao, W.4
  • 19
    • 80052915325 scopus 로고    scopus 로고
    • Recognizing human actions by attributes
    • J. Liu, B. Kuipers, and S. Savarese. Recognizing human actions by attributes. In CVPR, 2011.
    • (2011) CVPR
    • Liu, J.1    Kuipers, B.2    Savarese, S.3
  • 21
    • 84898772642 scopus 로고    scopus 로고
    • Pictorial human spaces. How well do humans perceive a 3D articulated pose?
    • E. Marinoiu, D. Papava, and C. Sminchisescu. Pictorial Human Spaces. How Well do Humans Perceive a 3D Articulated Pose? In ICCV, 2013.
    • (2013) ICCV
    • Marinoiu, E.1    Papava, D.2    Sminchisescu, C.3
  • 23
    • 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, 2013.
    • (2013) NIPS
    • Mikolov, T.1    Sutskever, I.2    Chen, K.3    Corrado, G.S.4    Dean, J.5
  • 24
    • 84976702763 scopus 로고
    • Wordnet: A lexical database for english
    • G. A. Miller. Wordnet: a lexical database for english. CACM, 38:39-41, 1995.
    • (1995) CACM , vol.38 , pp. 39-41
    • Miller, G.A.1
  • 25
    • 85041500875 scopus 로고    scopus 로고
    • Active segmentation with fixation
    • A. Mishra, Y. Aloimonos, and C. L. Fah. Active segmentation with fixation. In Proc. ICCV, pages 468-475, 2009.
    • (2009) Proc. ICCV , pp. 468-475
    • Mishra, A.1    Aloimonos, Y.2    Fah, C.L.3
  • 27
    • 65249121810 scopus 로고    scopus 로고
    • Automated flower classification over a large number of classes
    • M.-E. Nilsback and A. Zisserman. Automated flower classification over a large number of classes. In ICCVGI, 2008.
    • (2008) ICCVGI
    • Nilsback, M.-E.1    Zisserman, A.2
  • 30
  • 32
    • 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. In EMNLP, 2014.
    • (2014) EMNLP
    • Pennington, J.1    Socher, R.2    Manning, C.D.3
  • 33
    • 84856660881 scopus 로고    scopus 로고
    • Sparse dictionary-based representation and recognition of action attributes
    • Q. Qiu, Z. Jiang, and R. Chellappa. Sparse dictionary-based representation and recognition of action attributes. In ICCV, 2011.
    • (2011) ICCV
    • Qiu, Q.1    Jiang, Z.2    Chellappa, R.3
  • 35
    • 80052892795 scopus 로고    scopus 로고
    • Evaluating knowledge transfer and zero-shot learning in a large-scale setting
    • M. Rohrbach, M. Stark, and B.Schiele. Evaluating knowledge transfer and zero-shot learning in a large-scale setting. In CVPR, 2011.
    • (2011) CVPR
    • Rohrbach, M.1    Stark, M.2    Schiele, B.3
  • 36
    • 5044223783 scopus 로고    scopus 로고
    • Is bottom-up attention useful for object recognition?
    • U. Rutishauser, D. Walther, C. Koch, and P. Perona. Is bottom-up attention useful for object recognition? In CVPR, volume 2, 2004.
    • (2004) CVPR , vol.2
    • Rutishauser, U.1    Walther, D.2    Koch, C.3    Perona, P.4
  • 38
    • 84933553644 scopus 로고    scopus 로고
    • Prediction of search targets from fixations in open-world settings
    • H. Sattar, S. Müller, M. Fritz, and A. Bulling. Prediction of search targets from fixations in open-world settings. In CVPR, pages 981-990, 2015.
    • (2015) CVPR , pp. 981-990
    • Sattar, H.1    Müller, S.2    Fritz, M.3    Bulling, A.4
  • 40
    • 80052894348 scopus 로고    scopus 로고
    • Image ranking and retrieval based on multi-attribute queries
    • B. Siddiquie, R. Feris, and L. Davis. Image ranking and retrieval based on multi-attribute queries. In CVPR, 2011.
    • (2011) CVPR
    • Siddiquie, B.1    Feris, R.2    Davis, L.3
  • 42
    • 84455173231 scopus 로고    scopus 로고
    • Can computers learn from humans to see better?: Inferring scene semantics from viewers' eye movements
    • R. Subramanian, V. Yanulevskaya, and N. Sebe. Can computers learn from humans to see better?: inferring scene semantics from viewers' eye movements. In MM, pages 33-42, 2011.
    • (2011) MM , pp. 33-42
    • Subramanian, R.1    Yanulevskaya, V.2    Sebe, N.3
  • 45
    • 24944537843 scopus 로고    scopus 로고
    • Large margin methods for structured and interdependent output variables
    • I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun. Large margin methods for structured and interdependent output variables. JMLR, 2005.
    • (2005) JMLR
    • Tsochantaridis, I.1    Joachims, T.2    Hofmann, T.3    Altun, Y.4
  • 46
    • 77953177673 scopus 로고    scopus 로고
    • Joint learning of visual attributes, object classes and visual saliency
    • G. Wang and D. Forsyth. Joint learning of visual attributes, object classes and visual saliency. In ICCV, 2009.
    • (2009) ICCV
    • Wang, G.1    Forsyth, D.2
  • 47
    • 80052913382 scopus 로고    scopus 로고
    • A discriminative latent model of object classes and attributes
    • Y. Wang and G. Mori. A discriminative latent model of object classes and attributes. In ECCV, 2010.
    • (2010) ECCV
    • Wang, Y.1    Mori, G.2
  • 49
    • 84867117593 scopus 로고    scopus 로고
    • Wsabie: Scaling up to large vocabulary image annotation
    • J. Weston, S. Bengio, and N. Usunier. Wsabie: Scaling up to large vocabulary image annotation. In IJCAI, 2011.
    • (2011) IJCAI
    • Weston, J.1    Bengio, S.2    Usunier, N.3
  • 51
    • 84856672971 scopus 로고    scopus 로고
    • Human action recognition by learning bases of action attributes and parts
    • B. Yao, X. Jiang, A. Khosla, A. L. Lin, L. J. Guibas, and F.-F. Li. Human action recognition by learning bases of action attributes and parts. In ICCV, 2011.
    • (2011) ICCV
    • Yao, B.1    Jiang, X.2    Khosla, A.3    Lin, A.L.4    Guibas, L.J.5    Li, F.-F.6
  • 52
    • 84887396648 scopus 로고    scopus 로고
    • Studying relationships between human gaze, description, and computer vision
    • K. Yun, Y. Peng, D. Samaras, G. J. Zelinsky, and T. L. Berg. Studying relationships between human gaze, description, and computer vision. In CVPR, pages 739-746, 2013.
    • (2013) CVPR , pp. 739-746
    • Yun, K.1    Peng, Y.2    Samaras, D.3    Zelinsky, G.J.4    Berg, T.L.5


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.