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Volumn 2017-January, Issue , 2017, Pages 1042-1051

Zero-shot action recognition with error-correcting output codes

Author keywords

[No Author keywords available]

Indexed keywords

SEMANTICS;

EID: 85040705457     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.117     Document Type: Conference Paper
Times cited : (165)

References (65)
  • 1
    • 79955649703 scopus 로고    scopus 로고
    • Human activity analysis: A review
    • J. K. Aggarwal and M. S. Ryoo. Human activity analysis: A review. CSUR, 43(3):16:1-16:43, 2011.
    • (2011) CSUR , vol.43 , Issue.3 , pp. 161-1643
    • Aggarwal, J.K.1    Ryoo, M.S.2
  • 2
    • 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
  • 3
    • 24044435942 scopus 로고    scopus 로고
    • Reducing multiclass to binary: A unifying approach for margin classifiers
    • Sept
    • E. L. Allwein, R. E. Schapire, and Y. Singer. Reducing multiclass to binary: A unifying approach for margin classifiers. JMLR, 1:113-141, Sept. 2001.
    • (2001) JMLR , vol.1 , pp. 113-141
    • Allwein, E.L.1    Schapire, R.E.2    Singer, Y.3
  • 4
    • 84892868336 scopus 로고    scopus 로고
    • On the convergence of block coordinate descent type methods
    • A. Beck and L. Tetruashvili. On the convergence of block coordinate descent type methods. SIAM Journal on Optimization, 23(4):2037-2060, 2013.
    • (2013) SIAM Journal on Optimization , vol.23 , Issue.4 , pp. 2037-2060
    • Beck, A.1    Tetruashvili, L.2
  • 5
    • 85007202925 scopus 로고    scopus 로고
    • Dynamic concept composition for zero-example event detection
    • X. Chang, Y. Yang, G. Long, C. Zhang, and A. Hauptmann. Dynamic concept composition for zero-example event detection. In AAAI, 2016.
    • (2016) AAAI
    • Chang, X.1    Yang, Y.2    Long, G.3    Zhang, C.4    Hauptmann, A.5
  • 6
    • 85027917405 scopus 로고    scopus 로고
    • Improving human action recognition using fusion of depth camera and inertial sensors
    • C. Chen, R. Jafari, and N. Kehtarnavaz. Improving human action recognition using fusion of depth camera and inertial sensors. IEEE Transactions on Human-Machine Systems, 45(1):51-61, 2015.
    • (2015) IEEE Transactions on Human-Machine Systems , vol.45 , Issue.1 , pp. 51-61
    • Chen, C.1    Jafari, R.2    Kehtarnavaz, N.3
  • 7
    • 85006085657 scopus 로고    scopus 로고
    • 3d action recognition using multi-temporal depth motion maps and fisher vector
    • C. Chen, M. Liu, B. Zhang, J. Han, J. Jiang, and H. Liu. 3d action recognition using multi-temporal depth motion maps and fisher vector. In IJCAI, 2016.
    • (2016) IJCAI
    • Chen, C.1    Liu, M.2    Zhang, B.3    Han, J.4    Jiang, J.5    Liu, H.6
  • 8
    • 0000406788 scopus 로고
    • Solving multiclass learning problems via error-correcting output codes
    • Jan
    • T. G. Dietterich and G. Bakiri. Solving multiclass learning problems via error-correcting output codes. JAIR, 2(1):263-286, Jan. 1995.
    • (1995) JAIR , vol.2 , Issue.1 , pp. 263-286
    • Dietterich, T.G.1    Bakiri, G.2
  • 9
    • 34447532140 scopus 로고    scopus 로고
    • Boosted landmarks of contextual descriptors and forest-ecoc: A novel framework to detect and classify objects in cluttered scenes
    • S. Escalera, O. Pujol, and P. Radeva. Boosted landmarks of contextual descriptors and forest-ecoc: A novel framework to detect and classify objects in cluttered scenes. PRL, 28(13):1759 - 1768, 2007.
    • (2007) PRL , vol.28 , Issue.13 , pp. 1759-1768
    • Escalera, S.1    Pujol, O.2    Radeva, P.3
  • 10
    • 77949498817 scopus 로고    scopus 로고
    • Error-correcting output codes library
    • Feb
    • S. Escalera, O. Pujol, and P. Radeva. Error-correcting output codes library. JMLR, 11(Feb):661-664, 2010.
    • (2010) JMLR , vol.11 , pp. 661-664
    • Escalera, S.1    Pujol, O.2    Radeva, P.3
  • 11
    • 50949133669 scopus 로고    scopus 로고
    • Liblinear: A library for large linear classification
    • June
    • R.-E. Fan, K.-W. Chang, C.-J. Hsieh, X.-R. Wang, and C.J. Lin. Liblinear: A library for large linear classification. JMLR, 9:1871-1874, June 2008.
    • (2008) JMLR , vol.9 , pp. 1871-1874
    • Fan, R.-E.1    Chang, K.-W.2    Hsieh, C.-J.3    Wang, X.-R.4    Lin, C.J.5
  • 13
    • 84906482165 scopus 로고    scopus 로고
    • Transductive multi-view embedding for zero-shot recognition and annotation
    • Y. Fu, T. M. Hospedales, T. Xiang, Z. Fu, and S. Gong. Transductive multi-view embedding for zero-shot recognition and annotation. In ECCV, 2014.
    • (2014) ECCV
    • Fu, Y.1    Hospedales, T.M.2    Xiang, T.3    Fu, Z.4    Gong, S.5
  • 14
    • 84941001216 scopus 로고    scopus 로고
    • Transductive multi-view zero-shot learning
    • Nov
    • Y. Fu, T. M. Hospedales, T. Xiang, and S. Gong. Transductive multi-view zero-shot learning. IEEE TPAMI, 37(11):2332-2345, Nov 2015.
    • (2015) IEEE TPAMI , vol.37 , Issue.11 , pp. 2332-2345
    • Fu, Y.1    Hospedales, T.M.2    Xiang, T.3    Gong, S.4
  • 15
    • 84940993365 scopus 로고    scopus 로고
    • Zero-shot object recognition by semantic manifold distance
    • Z. Fu, T. Xiang, E. Kodirov, and S. Gong. Zero-shot object recognition by semantic manifold distance. In CVPR, 2015.
    • (2015) CVPR
    • Fu, Z.1    Xiang, T.2    Kodirov, E.3    Gong, S.4
  • 16
    • 84959256029 scopus 로고    scopus 로고
    • Exploring semantic inter-class relationships (sir) for zero-shot action recognition
    • C. Gan, M. Lin, Y. Yang, Y. Zhuang, and A. G. Hauptmann. Exploring semantic inter-class relationships (sir) for zero-shot action recognition. In AAAI, 2015.
    • (2015) AAAI
    • Gan, C.1    Lin, M.2    Yang, Y.3    Zhuang, Y.4    Hauptmann, A.G.5
  • 17
    • 84986281512 scopus 로고    scopus 로고
    • Learning attributes equals multi-source domain generalization
    • C. Gan, T. Yang, and B. Gong. Learning attributes equals multi-source domain generalization. In CVPR, 2016.
    • (2016) CVPR
    • Gan, C.1    Yang, T.2    Gong, B.3
  • 19
    • 80052874105 scopus 로고    scopus 로고
    • Iterative quantization: A pro-crustean approach to learning binary codes
    • Y. Gong and S. Lazebnik. Iterative quantization: A pro-crustean approach to learning binary codes. In CVPR, 2011.
    • (2011) CVPR
    • Gong, Y.1    Lazebnik, S.2
  • 20
    • 84937954530 scopus 로고    scopus 로고
    • Zero shot recognition with unreliable attributes
    • D. Jayaraman and K. Grauman. Zero shot recognition with unreliable attributes. In NIPS, 2014.
    • (2014) NIPS
    • Jayaraman, D.1    Grauman, K.2
  • 21
    • 84994341314 scopus 로고    scopus 로고
    • Manifold regularized cross-modal embedding for zero-shot learning
    • Z. Ji, Y. Yu, Y. Pang, J. Guo, and Z. Zhang. Manifold regularized cross-modal embedding for zero-shot learning. Information Sciences, 378:48 - 58, 2017.
    • (2017) Information Sciences , vol.378 , pp. 48-58
    • Ji, Z.1    Yu, Y.2    Pang, Y.3    Guo, J.4    Zhang, Z.5
  • 23
    • 84973901436 scopus 로고    scopus 로고
    • Unsupervised domain adaptation for zero-shot learning
    • E. Kodirov, T. Xiang, Z. Fu, and S. Gong. Unsupervised domain adaptation for zero-shot learning. In ICCV, 2015.
    • (2015) ICCV
    • Kodirov, E.1    Xiang, T.2    Fu, Z.3    Gong, S.4
  • 24
  • 25
    • 70450172710 scopus 로고    scopus 로고
    • Learning to detect unseen object classes by between-class attribute transfer
    • C. H. Lampert, H. Nickisch, and S. Harmeling. Learning to detect unseen object classes by between-class attribute transfer. In CVPR, 2009.
    • (2009) CVPR
    • Lampert, C.H.1    Nickisch, H.2    Harmeling, S.3
  • 26
    • 84894522762 scopus 로고    scopus 로고
    • Attribute-based classification for zero-shot visual object categorization
    • March
    • C. H. Lampert, H. Nickisch, and S. Harmeling. Attribute-based classification for zero-shot visual object categorization. IEEE TPAMI, 36(3):453-465, March 2014.
    • (2014) IEEE TPAMI , vol.36 , Issue.3 , pp. 453-465
    • Lampert, C.H.1    Nickisch, H.2    Harmeling, S.3
  • 27
    • 24944451092 scopus 로고    scopus 로고
    • On space-time interest points
    • I. Laptev. On space-time interest points. IJCV, 64(2):107-123, 2005.
    • (2005) IJCV , vol.64 , Issue.2 , pp. 107-123
    • Laptev, I.1
  • 28
    • 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
  • 30
    • 85044460692 scopus 로고    scopus 로고
    • Sequential discrete hashing for scalable cross-modality similarity retrieval
    • L. Liu, Z. Lin, L. Shao, F. Shen, G. Ding, and J. Han. Sequential discrete hashing for scalable cross-modality similarity retrieval. IEEE TIP, 2016.
    • (2016) IEEE TIP
    • Liu, L.1    Lin, Z.2    Shao, L.3    Shen, F.4    Ding, G.5    Han, J.6
  • 31
    • 84973924387 scopus 로고    scopus 로고
    • Projection bank: From high-dimensional data to medium-length binary codes
    • L. Liu, M. Yu, and L. Shao. Projection bank: From high-dimensional data to medium-length binary codes. In ICCV, 2015.
    • (2015) ICCV
    • Liu, L.1    Yu, M.2    Shao, L.3
  • 34
    • 85027713372 scopus 로고    scopus 로고
    • Attribute embedding with visual-semantic ambiguity removal for zero-shot learning
    • Y. Long, L. Liu, and L. Shao. Attribute embedding with visual-semantic ambiguity removal for zero-shot learning. In BMVC, 2016.
    • (2016) BMVC
    • Long, Y.1    Liu, L.2    Shao, L.3
  • 35
    • 85020195882 scopus 로고    scopus 로고
    • Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes
    • Y. Long, L. Liu, and L. Shao. Towards fine-grained open zero-shot learning: Inferring unseen visual features from attributes. In WACV, 2017.
    • (2017) WACV
    • Long, Y.1    Liu, L.2    Shao, L.3
  • 36
    • 57249084011 scopus 로고    scopus 로고
    • Visualizing data using t-sne
    • Nov
    • L. v. d. Maaten and G. Hinton. Visualizing data using t-sne. JMLR, 9:2579-2605, Nov 2008.
    • (2008) JMLR , vol.9 , pp. 2579-2605
    • Maaten, L.V.D.1    Hinton, G.2
  • 37
    • 84898956512 scopus 로고    scopus 로고
    • Distributed representations of words and phrases and their compositionality
    • T. Mikolov, I. Sutskever, and K. Chen. Distributed representations of words and phrases and their compositionality. In NIPS, 2013.
    • (2013) NIPS
    • Mikolov, T.1    Sutskever, I.2    Chen, K.3
  • 38
    • 84926034201 scopus 로고    scopus 로고
    • Evaluating neural word representations in tensor-based compositional settings
    • D. Milajevs, D. Kartsaklis, M. Sadrzadeh, and M. Purver. Evaluating neural word representations in tensor-based compositional settings. EMNLP, 2014.
    • (2014) EMNLP
    • Milajevs, D.1    Kartsaklis, D.2    Sadrzadeh, M.3    Purver, M.4
  • 39
    • 80052874353 scopus 로고    scopus 로고
    • Modeling temporal structure of decomposable motion segments for activity classification
    • J. C. Niebles, C.-W. Chen, and L. Fei-Fei. Modeling temporal structure of decomposable motion segments for activity classification. In ECCV, 2010.
    • (2010) ECCV
    • Niebles, J.C.1    Chen, C.-W.2    Fei-Fei, L.3
  • 41
    • 79959771606 scopus 로고    scopus 로고
    • Improving the fisher kernel for large-scale image classification
    • F. Perronnin, J. Sánchez, and T. Mensink. Improving the fisher kernel for large-scale image classification. In ECCV, 2010.
    • (2010) ECCV
    • Perronnin, F.1    Sánchez, J.2    Mensink, T.3
  • 42
    • 33645963453 scopus 로고    scopus 로고
    • Discriminant ecoc: A heuristic method for application dependent design of error correcting output codes
    • June
    • O. Pujol, P. Radeva, and J. Vitria. Discriminant ecoc: a heuristic method for application dependent design of error correcting output codes. IEEE TPAMI, 28(6):1007-1012, June 2006.
    • (2006) IEEE TPAMI , vol.28 , Issue.6 , pp. 1007-1012
    • Pujol, O.1    Radeva, P.2    Vitria, J.3
  • 43
    • 84994741654 scopus 로고    scopus 로고
    • Fast action retrieval from videos via feature disaggregation
    • J. Qin, L. Liu, M. Yu, Y. Wang, and L. Shao. Fast action retrieval from videos via feature disaggregation. CVIU, 156:104-116, 2017.
    • (2017) CVIU , vol.156 , pp. 104-116
    • Qin, J.1    Liu, L.2    Yu, M.3    Wang, Y.4    Shao, L.5
  • 44
    • 85009494321 scopus 로고    scopus 로고
    • Compressive sequential learning for action similarity labeling
    • Feb
    • J. Qin, L. Liu, Z. Zhang, Y. Wang, and L. Shao. Compressive sequential learning for action similarity labeling. IEEE TIP, 25(2):756-769, Feb 2016.
    • (2016) IEEE TIP , vol.25 , Issue.2 , pp. 756-769
    • Qin, J.1    Liu, L.2    Zhang, Z.3    Wang, Y.4    Shao, L.5
  • 45
    • 85027028866 scopus 로고    scopus 로고
    • Beyond semantic attributes: Discrete latent attributes learning for zero-shot recognition
    • Nov
    • J. Qin, Y. Wang, L. Liu, J. Chen, and L. Shao. Beyond semantic attributes: Discrete latent attributes learning for zero-shot recognition. IEEE SPL, 23(11):1667-1671, Nov 2016.
    • (2016) IEEE SPL , vol.23 , Issue.11 , pp. 1667-1671
    • Qin, J.1    Wang, Y.2    Liu, L.3    Chen, J.4    Shao, L.5
  • 46
    • 84969931523 scopus 로고    scopus 로고
    • An embarrassingly simple approach to zero-shot learning
    • B. Romera-Paredes and P. H. S. Torr. An embarrassingly simple approach to zero-shot learning. In ICML, 2015.
    • (2015) ICML
    • Romera-Paredes, B.1    Torr, P.H.S.2
  • 47
    • 0000988974 scopus 로고
    • A generalized solution of the orthogonal procrustes problem
    • P. H. Schönemann. A generalized solution of the orthogonal procrustes problem. Psychometrika, 31(1):1-10, 1966.
    • (1966) Psychometrika , vol.31 , Issue.1 , pp. 1-10
    • Schönemann, P.H.1
  • 48
    • 84962287497 scopus 로고    scopus 로고
    • Learning binary codes for maximum inner product search
    • F. Shen, W. Liu, S. Zhang, Y. Yang, and H. Tao Shen. Learning binary codes for maximum inner product search. In ICCV, 2015.
    • (2015) ICCV
    • Shen, F.1    Liu, W.2    Zhang, S.3    Yang, Y.4    Tao Shen, H.5
  • 51
    • 84995476598 scopus 로고    scopus 로고
    • A fast optimization method for general binary code learning
    • Dec
    • F. Shen, X. Zhou, Y. Yang, J. Song, H. T. Shen, and D. Tao. A fast optimization method for general binary code learning. IEEE TIP, 25(12):5610-5621, Dec 2016.
    • (2016) IEEE TIP , vol.25 , Issue.12 , pp. 5610-5621
    • Shen, F.1    Zhou, X.2    Yang, Y.3    Song, J.4    Shen, H.T.5    Tao, D.6
  • 52
    • 84937862424 scopus 로고    scopus 로고
    • Two-stream convolutional networks for action recognition in videos
    • K. Simonyan and A. Zisserman. Two-stream convolutional networks for action recognition in videos. In NIPS, pages 568-576, 2014.
    • (2014) NIPS , pp. 568-576
    • Simonyan, K.1    Zisserman, A.2
  • 54
    • 84973865953 scopus 로고    scopus 로고
    • Learning spatiotemporal features with 3d convolutional networks
    • D. Tran, L. Bourdev, R. Fergus, L. Torresani, and M. Paluri. Learning spatiotemporal features with 3d convolutional networks. In ICCV, 2015.
    • (2015) ICCV
    • Tran, D.1    Bourdev, L.2    Fergus, R.3    Torresani, L.4    Paluri, M.5
  • 55
    • 84898805910 scopus 로고    scopus 로고
    • Action recognition with improved trajectories
    • H. Wang and C. Schmid. Action recognition with improved trajectories. In ICCV, 2013.
    • (2013) ICCV
    • Wang, H.1    Schmid, C.2
  • 56
    • 84865410773 scopus 로고    scopus 로고
    • Semi-supervised hashing for large-scale search
    • J. Wang, S. Kumar, and S. F. Chang. Semi-supervised hashing for large-scale search. IEEE TPAMI, 34(12):2393-2406, 2012.
    • (2012) IEEE TPAMI , vol.34 , Issue.12 , pp. 2393-2406
    • Wang, J.1    Kumar, S.2    Chang, S.F.3
  • 59
    • 84956644623 scopus 로고    scopus 로고
    • Semantic embedding space for zero-shot action recognition
    • X. Xu, T. Hospedales, and S. Gong. Semantic embedding space for zero-shot action recognition. In ICIP, pages 63-67, 2015.
    • (2015) ICIP , pp. 63-67
    • Xu, X.1    Hospedales, T.2    Gong, S.3
  • 60
    • 85041929387 scopus 로고    scopus 로고
    • Multi-task zero-shot action recognition with prioritised data augmentation
    • X. Xu, T. Hospedales, and S. Gong. Multi-task zero-shot action recognition with prioritised data augmentation. In ECCV, 2016.
    • (2016) ECCV
    • Xu, X.1    Hospedales, T.2    Gong, S.3
  • 61
    • 84887368641 scopus 로고    scopus 로고
    • Designing category-level attributes for discriminative visual recognition
    • F. X. Yu, L. Cao, R. S. Feris, J. R. Smith, and S. F. Chang. Designing category-level attributes for discriminative visual recognition. In CVPR, 2013.
    • (2013) CVPR
    • Yu, F.X.1    Cao, L.2    Feris, R.S.3    Smith, J.R.4    Chang, S.F.5
  • 62
    • 84855413670 scopus 로고    scopus 로고
    • Attribute-based transfer learning for object categorization with zero/one training example
    • X. Yu and Y. Aloimonos. Attribute-based transfer learning for object categorization with zero/one training example. In ECCV, 2010.
    • (2010) ECCV
    • Yu, X.1    Aloimonos, Y.2
  • 63
    • 77953209151 scopus 로고    scopus 로고
    • Spectral error correcting output codes for efficient multiclass recognition
    • X. Zhang, L. Liang, and H.-Y. Shum. Spectral error correcting output codes for efficient multiclass recognition. In ICCV, 2009.
    • (2009) ICCV
    • Zhang, X.1    Liang, L.2    Shum, H.-Y.3
  • 64
    • 84986292720 scopus 로고    scopus 로고
    • Zero-shot learning via joint latent similarity embedding
    • Z. Zhang and V. Saligrama. Zero-shot learning via joint latent similarity embedding. In CVPR, 2016.
    • (2016) CVPR
    • Zhang, Z.1    Saligrama, V.2
  • 65
    • 84933555952 scopus 로고    scopus 로고
    • Sparse output coding for scalable visual recognition
    • B. Zhao and E. P. Xing. Sparse output coding for scalable visual recognition. IJCV, 119(1):60-75, 2016.
    • (2016) IJCV , vol.119 , Issue.1 , pp. 60-75
    • Zhao, B.1    Xing, E.P.2


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