메뉴 건너뛰기




Volumn 2016-December, Issue , 2016, Pages 845-853

HyperNet: Towards accurate region proposal generation and joint object detection

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER VISION; FEATURE EXTRACTION; OBJECT RECOGNITION; PATTERN RECOGNITION; SEMANTICS;

EID: 84986267173     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2016.98     Document Type: Conference Paper
Times cited : (948)

References (36)
  • 3
    • 84885880085 scopus 로고    scopus 로고
    • Object detection using stronglysupervised deformable part models
    • H. Azizpour and I. Laptev. Object detection using stronglysupervised deformable part models. In ECCV, 2012.
    • (2012) ECCV
    • Azizpour, H.1    Laptev, I.2
  • 4
    • 77956008665 scopus 로고    scopus 로고
    • Constrained parametric min-cuts for automatic object segmentation
    • J. Carreira and C. Sminchisescu. Constrained parametric min-cuts for automatic object segmentation. In CVPR, 2010.
    • (2010) CVPR
    • Carreira, J.1    Sminchisescu, C.2
  • 5
    • 84911456915 scopus 로고    scopus 로고
    • Bing: Binarized normed gradients for objectness estimation at 300fps
    • M.-M. Cheng, Z. Zhang, W.-Y. Lin, and P. Torr. Bing: Binarized normed gradients for objectness estimation at 300fps. In CVPR, 2014.
    • (2014) CVPR
    • Cheng, M.-M.1    Zhang, Z.2    Lin, W.-Y.3    Torr, P.4
  • 6
    • 33645146449 scopus 로고    scopus 로고
    • Histograms of oriented gradients for human detection
    • N. Dalal and B. Triggs. Histograms of oriented gradients for human detection. In CVPR, 2005.
    • (2005) CVPR
    • Dalal, N.1    Triggs, B.2
  • 7
    • 84903622275 scopus 로고    scopus 로고
    • Fast feature pyramids for object detection
    • P. Dollár, R. Appel, S. Belongie, and P. Perona. Fast feature pyramids for object detection. PAMI, 36 (8): 1532-1545, 2014.
    • (2014) PAMI , vol.36 , Issue.8 , pp. 1532-1545
    • Dollár, P.1    Appel, R.2    Belongie, S.3    Perona, P.4
  • 8
    • 84911443425 scopus 로고    scopus 로고
    • Scalable object detection using deep neural networks
    • D. Erhan, C. Szegedy, A. Toshev, and D. Anguelov. Scalable object detection using deep neural networks. In CVPR, 2014.
    • (2014) CVPR
    • Erhan, D.1    Szegedy, C.2    Toshev, A.3    Anguelov, D.4
  • 10
    • 77955422240 scopus 로고    scopus 로고
    • Object detection with discriminatively trained partbased models
    • P. F. Felzenszwalb, R. B. Girshick, D. McAllester, and D. Ramanan. Object detection with discriminatively trained partbased models. PAMI, 32 (9): 1627-1645, 2010.
    • (2010) PAMI , vol.32 , Issue.9 , pp. 1627-1645
    • Felzenszwalb, P.F.1    Girshick, R.B.2    McAllester, D.3    Ramanan, D.4
  • 11
  • 12
    • 84973864191 scopus 로고    scopus 로고
    • Object detection via a multiregion & semantic segmentation-aware cnn model
    • S. Gidaris and N. Komodakis. Object detection via a multiregion & semantic segmentation-aware cnn model. In ICCV, 2015.
    • (2015) ICCV
    • Gidaris, S.1    Komodakis, N.2
  • 13
    • 85029359197 scopus 로고    scopus 로고
    • Fast r-cnn
    • R. Girshick. Fast r-cnn. In ICCV, 2015.
    • (2015) ICCV
    • Girshick, R.1
  • 14
    • 84911400494 scopus 로고    scopus 로고
    • Rich feature hierarchies for accurate object detection and semantic segmentation
    • R. Girshick, J. Donahue, T. Darrell, and J. Malik. Rich feature hierarchies for accurate object detection and semantic segmentation. In CVPR, 2014.
    • (2014) CVPR
    • Girshick, R.1    Donahue, J.2    Darrell, T.3    Malik, J.4
  • 15
    • 84959236250 scopus 로고    scopus 로고
    • Hypercolumns for object segmentation and fine-grained localization
    • B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik. Hypercolumns for object segmentation and fine-grained localization. In CVPR, 2015.
    • (2015) CVPR
    • Hariharan, B.1    Arbeláez, P.2    Girshick, R.3    Malik, J.4
  • 16
    • 85009918748 scopus 로고    scopus 로고
    • Spatial pyramid pooling in deep convolutional networks for visual recognition
    • K. He, X. Zhang, S. Ren, and J. Sun. Spatial pyramid pooling in deep convolutional networks for visual recognition. In ECCV, 2014.
    • (2014) ECCV
    • He, K.1    Zhang, X.2    Ren, S.3    Sun, J.4
  • 18
    • 84973902476 scopus 로고    scopus 로고
    • Online object tracking with proposal selection
    • Y. Hua, K. Alahari, and C. Schmid. Online object tracking with proposal selection. In ICCV, 2015.
    • (2015) ICCV
    • Hua, Y.1    Alahari, K.2    Schmid, C.3
  • 19
    • 84898830857 scopus 로고    scopus 로고
    • Category-independent object-level saliency detection
    • Y. Jia and M. Han. Category-independent object-level saliency detection. In ICCV, 2013.
    • (2013) ICCV
    • Jia, Y.1    Han, M.2
  • 21
    • 84876231242 scopus 로고    scopus 로고
    • Imagenet classification with deep convolutional neural networks
    • A. Krizhevsky, I. Sutskever, and G. E. Hinton. Imagenet classification with deep convolutional neural networks. In NIPS, 2012.
    • (2012) NIPS
    • Krizhevsky, A.1    Sutskever, I.2    Hinton, G.E.3
  • 22
    • 84973861966 scopus 로고    scopus 로고
    • Deepbox: Learning objectness with convolutional networks
    • W. Kuo, B. Hariharan, and J. Malik. Deepbox: Learning objectness with convolutional networks. In ICCV, 2015.
    • (2015) ICCV
    • Kuo, W.1    Hariharan, B.2    Malik, J.3
  • 23
    • 84973863227 scopus 로고    scopus 로고
    • Learning to combine mid-level cues for object proposal generation
    • T. Lee, S. Fidler, and S. Dickinson. Learning to combine mid-level cues for object proposal generation. In ICCV, 2015.
    • (2015) ICCV
    • Lee, T.1    Fidler, S.2    Dickinson, S.3
  • 24
    • 84959205572 scopus 로고    scopus 로고
    • Fully convolutional networks for semantic segmentation
    • J. Long, E. Shelhamer, and T. Darrell. Fully convolutional networks for semantic segmentation. In CVPR, 2015.
    • (2015) CVPR
    • Long, J.1    Shelhamer, E.2    Darrell, T.3
  • 25
    • 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
  • 26
    • 84887391806 scopus 로고    scopus 로고
    • Occlusion patterns for object class detection
    • B. Pepikj, M. Stark, P. Gehler, and B. Schiele. Occlusion patterns for object class detection. In CVPR, 2013.
    • (2013) CVPR
    • Pepikj, B.1    Stark, M.2    Gehler, P.3    Schiele, B.4
  • 28
    • 84960980241 scopus 로고    scopus 로고
    • Faster r-cnn: Towards real-time object detection with region proposal networks
    • S. Ren, K. He, R. Girshick, and J. Sun. Faster r-cnn: Towards real-time object detection with region proposal networks. In NIPS, 2015.
    • (2015) NIPS
    • Ren, S.1    He, K.2    Girshick, R.3    Sun, J.4
  • 31
    • 85083951635 scopus 로고    scopus 로고
    • Overfeat: Integrated recognition, localization and detection using convolutional networks
    • P. Sermanet, D. Eigen, X. Zhang, M. Mathieu, R. Fergus, and Y. LeCun. Overfeat: Integrated recognition, localization and detection using convolutional networks. In ICLR, 2014.
    • (2014) ICLR
    • Sermanet, P.1    Eigen, D.2    Zhang, X.3    Mathieu, M.4    Fergus, R.5    LeCun, Y.6
  • 32
    • 85083953063 scopus 로고    scopus 로고
    • Very deep convolutional networks for large-scale image recognition
    • K. Simonyan and A. Zisserman. Very deep convolutional networks for large-scale image recognition. In ICLR, 2015.
    • (2015) ICLR
    • Simonyan, K.1    Zisserman, A.2
  • 34
    • 77956000059 scopus 로고    scopus 로고
    • An HOG-LBP human detector with partial occlusion handling
    • X. Wang, T. X. Han, and S. Yan. An hog-lbp human detector with partial occlusion handling. In CVPR, 2009.
    • (2009) CVPR
    • Wang, X.1    Han, T.X.2    Yan, S.3
  • 35
    • 84978839486 scopus 로고    scopus 로고
    • Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction
    • Y. Zhang, K. Sohn, R. Villegas, G. Pan, and H. Lee. Improving object detection with deep convolutional networks via Bayesian optimization and structured prediction. In CVPR, 2014.
    • (2014) CVPR
    • Zhang, Y.1    Sohn, K.2    Villegas, R.3    Pan, G.4    Lee, H.5
  • 36
    • 85009853104 scopus 로고    scopus 로고
    • Edge boxes: Locating object proposals from edges
    • C. L. Zitnick and P. Dollár. Edge boxes: Locating object proposals from edges. In ECCV, 2014.
    • (2014) ECCV
    • Zitnick, C.L.1    Dollár, P.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.