메뉴 건너뛰기




Volumn 07-12-June-2015, Issue , 2015, Pages 833-841

Cross-scene crowd counting via deep convolutional neural networks

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; CONVOLUTION; NEURAL NETWORKS;

EID: 84959214343     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2015.7298684     Document Type: Conference Paper
Times cited : (1350)

References (31)
  • 1
    • 35148836705 scopus 로고    scopus 로고
    • Face recognition using kernel ridge regression
    • S. An, W. Liu, and S. Venkatesh. Face recognition using kernel ridge regression. In CVPR, 2007
    • (2007) CVPR
    • An, S.1    Liu, W.2    Venkatesh, S.3
  • 3
    • 33845582996 scopus 로고    scopus 로고
    • Unsupervised Bayesian detection of independent motion in crowds
    • G. J. Brostow and R. Cipolla. Unsupervised Bayesian detection of independent motion in crowds. In CVPR, 2006
    • (2006) CVPR
    • Brostow, G.J.1    Cipolla, R.2
  • 4
    • 51949104316 scopus 로고    scopus 로고
    • Privacy preserving crowd monitoring: Counting people without people models or tracking
    • A. B. Chan, Z. S. Liang, and N. Vasconcelos. Privacy preserving crowd monitoring: Counting people without people models or tracking. In CVPR, 2008
    • (2008) CVPR
    • Chan, A.B.1    Liang, Z.S.2    Vasconcelos, N.3
  • 5
    • 84887355589 scopus 로고    scopus 로고
    • Cumulative attribute space for age and crowd density estimation
    • K. Chen, S. Gong, T. Xiang, Q. Mary, and C. C. Loy. Cumulative attribute space for age and crowd density estimation. In CVPR, 2013
    • (2013) CVPR
    • Chen, K.1    Gong, S.2    Xiang, T.3    Mary, Q.4    Loy, C.C.5
  • 6
    • 84898455547 scopus 로고    scopus 로고
    • Feature mining for localised crowd counting
    • K. Chen, C. C. Loy, S. Gong, and T. Xiang. Feature mining for localised crowd counting. In BMVC, 2012
    • (2012) BMVC
    • Chen, K.1    Loy, C.C.2    Gong, S.3    Xiang, T.4
  • 7
    • 84874563522 scopus 로고    scopus 로고
    • Learning to count with regression forest and structured labels
    • L. Fiaschi, R. Nair, U. Koethe, and F. A. Hamprecht. Learning to count with regression forest and structured labels. In ICPR, 2012
    • (2012) ICPR
    • Fiaschi, L.1    Nair, R.2    Koethe, U.3    Hamprecht, F.A.4
  • 8
    • 84887356947 scopus 로고    scopus 로고
    • Multi-source multi-scale counting in extremely dense crowd images
    • H. Idrees, I. Saleemi, and M. Shah. Multi-source multi-scale counting in extremely dense crowd images. In CVPR, 2013
    • (2013) CVPR
    • Idrees, H.1    Saleemi, I.2    Shah, M.3
  • 9
    • 84959217725 scopus 로고    scopus 로고
    • Deeply learned attributes for crowd scene understanding
    • S. Jing, K. Kai, L. Chen, Chang, and W. Xiaogang. Deeply learned attributes for crowd scene understanding. In CVPR, 2015
    • (2015) CVPR
    • Jing, S.1    Kai, K.2    Chen, L.3    Chang, X.W.4
  • 11
    • 34147092059 scopus 로고    scopus 로고
    • A viewpoint invariant approach for crowd counting
    • D. Kong, D. Gray, and H. Tao. A viewpoint invariant approach for crowd counting. In ICPR, 2006
    • (2006) ICPR
    • Kong, D.1    Gray, D.2    Tao, H.3
  • 12
    • 85162384490 scopus 로고    scopus 로고
    • Learning to count objects in images
    • V. Lempitsky and A. Zisserman. Learning to count objects in images. In NIPS, 2010
    • (2010) NIPS
    • Lempitsky, V.1    Zisserman, A.2
  • 13
    • 84911383794 scopus 로고    scopus 로고
    • Deepreid: Deep filter pairing neural network for person re-identification
    • W. Li, R. Zhao, T. Xiao, and X. Wang. Deepreid: Deep filter pairing neural network for person re-identification. In CVPR, 2014
    • (2014) CVPR
    • Li, W.1    Zhao, R.2    Xiao, T.3    Wang, X.4
  • 14
    • 77649270941 scopus 로고    scopus 로고
    • Shape-based human detection and segmentation via hierarchical part-template matching
    • Z. Lin and L. S. Davis. Shape-based human detection and segmentation via hierarchical part-template matching. TPAMI, 32(4):604-618, 2010
    • (2010) TPAMI , vol.32 , Issue.4 , pp. 604-618
    • Lin, Z.1    Davis, L.S.2
  • 15
    • 79953049203 scopus 로고    scopus 로고
    • Sift flow: Dense correspondence across scenes and its applications
    • C. Liu, J. Yuen, and A. Torralba. Sift flow: Dense correspondence across scenes and its applications. TPAMI, 33:978-994, 2011
    • (2011) TPAMI , vol.33 , pp. 978-994
    • Liu, C.1    Yuen, J.2    Torralba, A.3
  • 16
    • 3042535216 scopus 로고    scopus 로고
    • Distinctive image features from scale-invariant keypoints
    • D. G. Lowe. Distinctive image features from scale-invariant keypoints. IJCV, 60(2):91-110, 2004
    • (2004) IJCV , vol.60 , Issue.2 , pp. 91-110
    • Lowe, D.G.1
  • 17
    • 84898795504 scopus 로고    scopus 로고
    • From semi-supervised to transfer counting of crowds
    • C. C. Loy, S. Gong, and T. Xiang. From semi-supervised to transfer counting of crowds. In ICCV, 2013
    • (2013) ICCV
    • Loy, C.C.1    Gong, S.2    Xiang, T.3
  • 18
    • 85052589820 scopus 로고    scopus 로고
    • On the efficacy of texture analysis for crowd monitoring
    • IEEE
    • A. Marana, L. d. F. Costa, R. Lotufo, and S. Velastin. On the efficacy of texture analysis for crowd monitoring. In SIBGRAPI, pages 354-361. IEEE, 1998
    • (1998) SIBGRAPI , pp. 354-361
    • Marana, A.1    Costa, D.F.L.2    Lotufo, R.3    Velastin, S.4
  • 19
    • 0036647193 scopus 로고    scopus 로고
    • Multiresolution gray-scale and rotation invariant texture classification with local binary patterns
    • T. Ojala, M. Pietikainen, and T. Maenpaa. Multiresolution gray-scale and rotation invariant texture classification with local binary patterns. TPAMI, 24(7):971-987, 2002
    • (2002) TPAMI , vol.24 , Issue.7 , pp. 971-987
    • Ojala, T.1    Pietikainen, M.2    Maenpaa, T.3
  • 20
    • 84898788725 scopus 로고    scopus 로고
    • Joint deep learning for pedestrian detection
    • W. Ouyang and X. Wang. Joint deep learning for pedestrian detection. In ICCV, 2013
    • (2013) ICCV
    • Ouyang, W.1    Wang, X.2
  • 21
    • 33845571601 scopus 로고    scopus 로고
    • Counting crowded moving objects
    • V. Rabaud and S. Belongie. Counting crowded moving objects. In CVPR, 2006
    • (2006) CVPR
    • Rabaud, V.1    Belongie, S.2
  • 26
    • 80052891892 scopus 로고    scopus 로고
    • Superparsing: Scalable nonparametric image parsing with superpixels
    • Springer
    • J. Tighe and S. Lazebnik. Superparsing: scalable nonparametric image parsing with superpixels. In ECCV. Springer, 2010
    • (2010) ECCV
    • Tighe, J.1    Lazebnik, S.2
  • 27
    • 80052885969 scopus 로고    scopus 로고
    • Automatic adaptation of a generic pedestrian detector to a specific traffic scene
    • M. Wang and X. Wang. Automatic adaptation of a generic pedestrian detector to a specific traffic scene. In CVPR, 2011
    • (2011) CVPR
    • Wang, M.1    Wang, X.2
  • 28
    • 84898957022 scopus 로고    scopus 로고
    • Learning a deep compact image representation for visual tracking
    • N. Wang and D.-Y. Yeung. Learning a deep compact image representation for visual tracking. In NIPS, 2013
    • (2013) NIPS
    • Wang, N.1    Yeung, D.-Y.2
  • 29
    • 33745943636 scopus 로고    scopus 로고
    • Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors
    • B. Wu and R. Nevatia. Detection of multiple, partially occluded humans in a single image by Bayesian combination of edgelet part detectors. In ICCV, 2005
    • (2005) ICCV
    • Wu, B.1    Nevatia, R.2
  • 30
    • 84952035580 scopus 로고    scopus 로고
    • Deep learning of scene-specific classifier for pedestrian detection
    • X. Zeng, W. Ouyang, M. Wang, and X. Wang. Deep learning of scene-specific classifier for pedestrian detection. In ECCV. 2014
    • (2014) ECCV
    • Zeng, X.1    Ouyang, W.2    Wang, M.3    Wang, X.4
  • 31
    • 84898828144 scopus 로고    scopus 로고
    • Multi-stage contextual deep learning for pedestrian detection
    • X. Zeng, W. Ouyang, and X. Wang. Multi-stage contextual deep learning for pedestrian detection. In ICCV, 2013.
    • (2013) ICCV
    • Zeng, X.1    Ouyang, W.2    Wang, X.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.