메뉴 건너뛰기




Volumn 113, Issue 1, 2015, Pages 19-36

Heterogeneous Multi-task Learning for Human Pose Estimation with Deep Convolutional Neural Network

Author keywords

Deep Learning; Human Pose Estimation

Indexed keywords

CONVOLUTION; DEEP LEARNING; NETWORK ARCHITECTURE; NETWORK LAYERS; NEURAL NETWORKS;

EID: 84939885143     PISSN: 09205691     EISSN: 15731405     Source Type: Journal    
DOI: 10.1007/s11263-014-0767-8     Document Type: Article
Times cited : (84)

References (34)
  • 1
  • 4
    • 84898906904 scopus 로고    scopus 로고
    • Better appearance models for pictorial structures. In: British Machine Vision Conference
    • Eichner, M., & Ferrari, V. (2009a) Better appearance models for pictorial structures. In: British Machine Vision Conference, pp 1–11.
    • (2009) pp 1–11
    • Eichner, M.1    Ferrari, V.2
  • 5
    • 84939901262 scopus 로고    scopus 로고
    • Ferrari, V, Upper body detector:
    • Eichner, M., & Ferrari, V. (2009b) Upper body detector. http://groups.inf.ed.ac.uk/calvin/calvin_upperbody_detector/
    • (2009)
    • Eichner, M.1
  • 7
    • 84866644964 scopus 로고    scopus 로고
    • Ferrari, V: Human pose co-estimation and applications. IEEE Trans Pattern Anal Mach Intell
    • Eichner, M., & Ferrari, V. (2012). Human pose co-estimation and applications. IEEE Trans Pattern Anal Mach Intell.
    • (2012)
    • Eichner, M.1
  • 16
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks. In, Neural Information Processing Systems:
    • Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2012) Imagenet classification with deep convolutional neural networks. In: Neural Information Processing Systems.
    • (2012)
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.3
  • 21
    • 84887351384 scopus 로고    scopus 로고
    • Poselet conditioned pictorial structures. In: IEEE Conference on Computer Vision and Pattern Recognition
    • Pishchulin, L., Andriluka, M., Gehler, P., & Schiele, B. (2013) Poselet conditioned pictorial structures. In: IEEE Conference on Computer Vision and Pattern Recognition, pp 588–595.
    • (2013) pp 588–595
    • Pishchulin, L.1    Andriluka, M.2    Gehler, P.3    Schiele, B.4
  • 22
    • 84939901273 scopus 로고    scopus 로고
    • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1988). Learning representations by back-propagating errors. In J. A. Anderson & E. Rosenfeld (Eds.), Neurocomputing: Foundations of research. Cambridge, MA: MIT Press
    • Rumelhart, D. E., Hinton, G. E., & Williams, R. J. (1988). Learning representations by back-propagating errors. In J. A. Anderson & E. Rosenfeld (Eds.), Neurocomputing: Foundations of research (pp. 696–699). Cambridge, MA: MIT Press.
  • 29
    • 56449119888 scopus 로고    scopus 로고
    • Deep learning via semi-supervised embedding. In: International Conference on Machine Learning
    • Weston, J., Ratle, F., & Collobert, R. (2008) Deep learning via semi-supervised embedding. In: International Conference on Machine Learning.
    • (2008) & Collobert, R
    • Weston, J.1    Ratle, F.2
  • 33
    • 31844442664 scopus 로고    scopus 로고
    • Learning gaussian processes from multiple tasks. In: International Conference on Machine Learning
    • Yu, K., Tresp, V., & Schwaighofer, A. (2005) Learning gaussian processes from multiple tasks. In: International Conference on Machine Learning, pp 1012–1019.
    • (2005) pp 1012–1019
    • Yu, K.1    Tresp, V.2    Schwaighofer, A.3
  • 34
    • 84906489074 scopus 로고    scopus 로고
    • Zeiler, M. D., & Fergus, R. (2014). Visualizing and understanding convolutional networks. In Computer Vision – ECCV 2014. Lecture Notes in Computer Science. Springer
    • Zeiler, M. D., & Fergus, R. (2014). Visualizing and understanding convolutional networks. In Computer Vision – ECCV 2014. Lecture Notes in Computer Science (Vol. 8689, pp. 818–833). Springer.


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.