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Volumn 2017-January, Issue , 2017, Pages 645-654

Split-brain autoencoders: Unsupervised learning by cross-channel prediction

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; FORECASTING; LEARNING SYSTEMS;

EID: 85044323260     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2017.76     Document Type: Conference Paper
Times cited : (739)

References (48)
  • 2
    • 27844439373 scopus 로고    scopus 로고
    • A framework for learning predictive structures from multiple tasks and unlabeled data
    • Nov
    • R. K. Ando and T. Zhang. A framework for learning predictive structures from multiple tasks and unlabeled data. Journal of Machine Learning Research, 6(Nov):1817-1853, 2005.
    • (2005) Journal of Machine Learning Research , vol.6 , pp. 1817-1853
    • Ando, R.K.1    Zhang, T.2
  • 10
    • 84973897611 scopus 로고    scopus 로고
    • Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
    • D. Eigen and R. Fergus. Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture. In Proceedings of the IEEE International Conference on Computer Vision, pages 2650-2658, 2015.
    • (2015) Proceedings of The IEEE International Conference on Computer Vision , pp. 2650-2658
    • Eigen, D.1    Fergus, R.2
  • 16
    • 84906344142 scopus 로고    scopus 로고
    • Learning rich features from rgb-d images for object detection and segmentation
    • Springer
    • S. Gupta, R. Girshick, P. Arbeláez, and J. Malik. Learning rich features from rgb-d images for object detection and segmentation. In European Conference on Computer Vision, pages 345-360. Springer, 2014.
    • (2014) European Conference on Computer Vision , pp. 345-360
    • Gupta, S.1    Girshick, R.2    Arbeláez, P.3    Malik, J.4
  • 18
    • 84986274465 scopus 로고    scopus 로고
    • Deep residual learning for image recognition
    • K. He, X. Zhang, S. Ren, and J. Sun. Deep residual learning for image recognition. CVPR, 2016.
    • (2016) CVPR
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 19
    • 33746600649 scopus 로고    scopus 로고
    • Reducing the dimensionality of data with neural networks
    • G. E. Hinton and R. R. Salakhutdinov. Reducing the dimensionality of data with neural networks. Science, 313(5786):504-507, 2006.
    • (2006) Science , vol.313 , Issue.5786 , pp. 504-507
    • Hinton, G.E.1    Salakhutdinov, R.R.2
  • 20
    • 84980049328 scopus 로고    scopus 로고
    • Let there be Color!: Joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
    • S. Iizuka, E. Simo-Serra, and H. Ishikawa. Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification. ACM Transactions on Graphics (Proc. of SIGGRAPH 2016), 35(4), 2016.
    • (2016) ACM Transactions on Graphics (Proc. of SIGGRAPH 2016) , vol.35 , Issue.4
    • Iizuka, S.1    Simo-Serra, E.2    Ishikawa, H.3
  • 27
    • 85041897195 scopus 로고    scopus 로고
    • Colorization as a proxy task for visual understanding
    • G. Larsson, M. Maire, and G. Shakhnarovich. Colorization as a proxy task for visual understanding. CVPR, 2017.
    • (2017) CVPR
    • Larsson, G.1    Maire, M.2    Shakhnarovich, G.3
  • 29
    • 84990036780 scopus 로고    scopus 로고
    • Shuffle and learn: Unsupervised learning using temporal order verification
    • Springer
    • I. Misra, C. L. Zitnick, and M. Hebert. Shuffle and learn: unsupervised learning using temporal order verification. In European Conference on Computer Vision, pages 527-544. Springer, 2016.
    • (2016) European Conference on Computer Vision , pp. 527-544
    • Misra, I.1    Zitnick, C.L.2    Hebert, M.3
  • 30
    • 84986287885 scopus 로고    scopus 로고
    • Unsupervised learning of visual representations by solving jigsaw puzzles
    • M. Noroozi and P. Favaro. Unsupervised learning of visual representations by solving jigsaw puzzles. European Conference on Computer Vision, 2016.
    • (2016) European Conference on Computer Vision
    • Noroozi, M.1    Favaro, P.2
  • 37
    • 73249147662 scopus 로고    scopus 로고
    • Deep boltzmann machines
    • R. Salakhutdinov and G. E. Hinton. Deep boltzmann machines. In AISTATS, volume 1, page 3, 2009.
    • (2009) AISTATS , vol.1 , pp. 3
    • Salakhutdinov, R.1    Hinton, G.E.2
  • 40
    • 0000329993 scopus 로고
    • Information processing in dynamical systems: Foundations of harmony theory
    • DTIC Document
    • P. Smolensky. Information processing in dynamical systems: Foundations of harmony theory. Technical report, DTIC Document, 1986.
    • (1986) Technical Report
    • Smolensky, P.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.