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Volumn , Issue , 2016, Pages 781-790

Play and rewind: Optimizing binary representations of videos by self-supervised temporal hashing

Author keywords

Binary LSTM; Sequence learning; Temporal hashing; Video retrieval

Indexed keywords

BINARY CODES; CODES (SYMBOLS); HASH FUNCTIONS; IMAGE RETRIEVAL; OPTIMIZATION;

EID: 84994589377     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2964284.2964308     Document Type: Conference Paper
Times cited : (97)

References (43)
  • 2
    • 85162311477 scopus 로고    scopus 로고
    • Picodes: Learning a compact code for novel-category recognition
    • A. Bergamo, L. Torresani, and A. W. Fitzgibbon. Picodes: Learning a compact code for novel-category recognition. In NIPS, 2011.
    • (2011) NIPS
    • Bergamo, A.1    Torresani, L.2    Fitzgibbon, A.W.3
  • 3
    • 84871390155 scopus 로고    scopus 로고
    • Submodular video hashing: A unified framework towards video pooling and indexing
    • L. Cao, Z. Li, Y. Mu, and S.-F. Chang. Submodular video hashing: a unified framework towards video pooling and indexing. In MM, 2012.
    • (2012) MM
    • Cao, L.1    Li, Z.2    Mu, Y.3    Chang, S.-F.4
  • 6
    • 84994612935 scopus 로고    scopus 로고
    • Learning to hash with binary deep neural network
    • T.-T. Do, A.-D. Doan, and N.-M. Cheung. Learning to hash with binary deep neural network. In ECCV, 2016.
    • (2016) ECCV
    • Do, T.-T.1    Doan, A.-D.2    Cheung, N.-M.3
  • 9
    • 15044355327 scopus 로고    scopus 로고
    • Similarity search in high dimensions via hashing
    • A. Gionis, P. Indyk, R. Motwani, et al. Similarity search in high dimensions via hashing. In VLDB, 1999.
    • (1999) VLDB
    • Gionis, A.1    Indyk, P.2    Motwani, R.3
  • 10
    • 84872555593 scopus 로고    scopus 로고
    • Deep sparse rectifier neural networks
    • X. Glorot, A. Bordes, and Y. Bengio. Deep sparse rectifier neural networks. In ICAIS, 2011.
    • (2011) ICAIS
    • Glorot, X.1    Bordes, A.2    Bengio, Y.3
  • 11
    • 84887601251 scopus 로고    scopus 로고
    • Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval
    • Y. Gong, S. Lazebnik, A. Gordo, and F. Perronnin. Iterative quantization: A procrustean approach to learning binary codes for large-scale image retrieval. TPAMI, 2013.
    • (2013) TPAMI
    • Gong, Y.1    Lazebnik, S.2    Gordo, A.3    Perronnin, F.4
  • 12
    • 27744588611 scopus 로고    scopus 로고
    • Framewise phoneme classification with bidirectional lstm and other neural network architectures
    • A. Graves and J. Schmidhuber. Framewise phoneme classification with bidirectional lstm and other neural network architectures. Neural Networks, 2005.
    • (2005) Neural Networks
    • Graves, A.1    Schmidhuber, J.2
  • 13
    • 0000844603 scopus 로고    scopus 로고
    • Some optimal inapproximability results
    • J. Håstad. Some optimal inapproximability results. JACM, 2001.
    • (2001) JACM
    • Håstad, J.1
  • 14
    • 80054815184 scopus 로고    scopus 로고
    • A survey on visual content-based video indexing and retrieval
    • W. Hu, N. Xie, L. Li, X. Zeng, and S. Maybank. A survey on visual content-based video indexing and retrieval. TSMC Part C, 2011.
    • (2011) TSMC Part C
    • Hu, W.1    Xie, N.2    Li, L.3    Zeng, X.4    Maybank, S.5
  • 17
    • 77955006337 scopus 로고    scopus 로고
    • Content-based multimedia information retrieval: State of the art and challenges
    • M. S. Lew, N. Sebe, C. Djeraba, and R. Jain. Content-based multimedia information retrieval: State of the art and challenges. TOMM, 2006.
    • (2006) TOMM
    • Lew, M.S.1    Sebe, N.2    Djeraba, C.3    Jain, R.4
  • 18
    • 84978634548 scopus 로고    scopus 로고
    • Multimodal visual pattern mining with convolutional neural networks
    • H. Li. Multimodal visual pattern mining with convolutional neural networks. In ICMR, 2016.
    • (2016) ICMR
    • Li, H.1
  • 19
    • 84866714589 scopus 로고    scopus 로고
    • Fast search in hamming space with multi-index hashing
    • M. Norouzi, A. Punjani, and D. J. Fleet. Fast search in hamming space with multi-index hashing. In CVPR, 2012.
    • (2012) CVPR
    • Norouzi, M.1    Punjani, A.2    Fleet, D.J.3
  • 21
    • 84887375149 scopus 로고    scopus 로고
    • Event retrieval in large video collections with circulant temporal encoding
    • J. Revaud, M. Douze, C. Schmid, and H. Jégou. Event retrieval in large video collections with circulant temporal encoding. In CVPR, 2013.
    • (2013) CVPR
    • Revaud, J.1    Douze, M.2    Schmid, C.3    Jégou, H.4
  • 25
    • 68349121465 scopus 로고    scopus 로고
    • Concept-based video retrieval
    • C. G. Snoek and M. Worring. Concept-based video retrieval. FTIR, 2008.
    • (2008) FTIR
    • Snoek, C.G.1    Worring, M.2
  • 26
    • 84455173075 scopus 로고    scopus 로고
    • Multiple feature hashing for real-time large scale near-duplicate video retrieval
    • J. Song, Y. Yang, Z. Huang, H. T. Shen, and R. Hong. Multiple feature hashing for real-time large scale near-duplicate video retrieval. In MM, 2011.
    • (2011) MM
    • Song, J.1    Yang, Y.2    Huang, Z.3    Shen, H.T.4    Hong, R.5
  • 27
    • 84969544782 scopus 로고    scopus 로고
    • Unsupervised learning of video representations using lstms
    • N. Srivastava, E. Mansimov, and R. Salakhudinov. Unsupervised learning of video representations using lstms. In ICML, 2015.
    • (2015) ICML
    • Srivastava, N.1    Mansimov, E.2    Salakhudinov, R.3
  • 28
    • 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, 2014.
    • (2014) NIPS
    • Sutskever, I.1    Vinyals, O.2    Le, Q.V.3
  • 30
    • 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, 2015.
    • (2015) CVPR
    • Vinyals, O.1    Toshev, A.2    Bengio, S.3    Erhan, D.4
  • 31
    • 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
  • 32
    • 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. TPAMI, 2012.
    • (2012) TPAMI
    • Wang, J.1    Kumar, S.2    Chang, S.-F.3
  • 35
    • 84986250477 scopus 로고    scopus 로고
    • Harnessing object and scene semantics for large-scale video understanding
    • Z. Wu, Y. Fu, Y.-G. Jiang, and L. Sigal. Harnessing object and scene semantics for large-scale video understanding. In CVPR, 2016.
    • (2016) CVPR
    • Wu, Z.1    Fu, Y.2    Jiang, Y.-G.3    Sigal, L.4
  • 36
    • 77955988947 scopus 로고    scopus 로고
    • Sun database: Large-scale scene recognition from abbey to zoo
    • J. Xiao, J. Hays, K. A. Ehinger, A. Oliva, and A. Torralba. Sun database: Large-scale scene recognition from abbey to zoo. In CVPR, 2010.
    • (2010) CVPR
    • Xiao, J.1    Hays, J.2    Ehinger, K.A.3    Oliva, A.4    Torralba, A.5
  • 37
    • 84907908987 scopus 로고    scopus 로고
    • Exploiting web images for semantic video indexing via robust sample-specific loss
    • Y. Yang, Z.-J. Zha, Y. Gao, X. Zhu, and T.-S. Chua. Exploiting web images for semantic video indexing via robust sample-specific loss. TMM, 2014.
    • (2014) TMM
    • Yang, Y.1    Zha, Z.-J.2    Gao, Y.3    Zhu, X.4    Chua, T.-S.5
  • 38
    • 84994561753 scopus 로고    scopus 로고
    • Large-scale video hashing via structure learning
    • G. Ye, D. Liu, J. Wang, and S.-F. Chang. Large-scale video hashing via structure learning. In CVPR, 2013.
    • (2013) CVPR
    • Ye, G.1    Liu, D.2    Wang, J.3    Chang, S.-F.4
  • 42
    • 84887498863 scopus 로고    scopus 로고
    • Attribute-augmented semantic hierarchy: Towards bridging semantic gap and intention gap in image retrieval
    • H. Zhang, Z.-J. Zha, Y. Yang, S. Yan, Y. Gao, and T.-S. Chua. Attribute-augmented semantic hierarchy: towards bridging semantic gap and intention gap in image retrieval. In MM, 2013.
    • (2013) MM
    • Zhang, H.1    Zha, Z.-J.2    Yang, Y.3    Yan, S.4    Gao, Y.5    Chua, T.-S.6
  • 43
    • 84959240114 scopus 로고    scopus 로고
    • Deep semantic ranking based hashing for multi-label image retrieval
    • F. Zhao, Y. Huang, L. Wang, and T. Tan. Deep semantic ranking based hashing for multi-label image retrieval. In CVPR, 2015.
    • (2015) CVPR
    • Zhao, F.1    Huang, Y.2    Wang, L.3    Tan, T.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.