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Volumn , Issue , 2014, Pages 336-343

RIGOR: Reusing inference in graph cuts for generating object regions

Author keywords

Boosting; Graph Cuts; Object Proposals; Object Segmentation; Reuse

Indexed keywords

GRAPH ALGORITHMS; GRAPHIC METHODS; LAKES; OBJECT RECOGNITION;

EID: 84911456672     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.50     Document Type: Conference Paper
Times cited : (113)

References (35)
  • 2
    • 79953048649 scopus 로고    scopus 로고
    • Contour detection and hierarchical image segmentation
    • P. Arbelaez, M. Maire, C. Fowlkes, and J. Malik. Contour detection and hierarchical image segmentation. PAMI, 33(5):898-916, 2011.
    • (2011) PAMI , vol.33 , Issue.5 , pp. 898-916
    • Arbelaez, P.1    Maire, M.2    Fowlkes, C.3    Malik, J.4
  • 4
    • 0034844730 scopus 로고    scopus 로고
    • Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images
    • Y. Boykov and M.-P. Jolly. Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images. In CVPR, pages 105-112 vol.1, 2001.
    • (2001) CVPR , vol.1 , pp. 105-112
    • Boykov, Y.1    Jolly, M.-P.2
  • 5
    • 4344598245 scopus 로고    scopus 로고
    • An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision
    • Y. Boykov and V. Kolmogorov. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. PAMI, 26(9):1124-1137, 2004.
    • (2004) PAMI , vol.26 , Issue.9 , pp. 1124-1137
    • Boykov, Y.1    Kolmogorov, V.2
  • 6
    • 84861335581 scopus 로고    scopus 로고
    • CPMC: Automatic object segmentation using constrained parametric min-cuts
    • J. Carreira and C. Sminchisescu. CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts. PAMI, 34(7):1312-1328, 2012.
    • (2012) PAMI , vol.34 , Issue.7 , pp. 1312-1328
    • Carreira, J.1    Sminchisescu, C.2
  • 7
    • 0000891810 scopus 로고
    • Algorithm for solution of a problem of maximum flow in networks with power estimation
    • E. A. Dinic. Algorithm for solution of a problem of maximum flow in networks with power estimation. Soviet Math. Dokl, 11(5):1277-1280, 1970.
    • (1970) Soviet Math. Dokl , vol.11 , Issue.5 , pp. 1277-1280
    • Dinic, E.A.1
  • 8
    • 84898820142 scopus 로고    scopus 로고
    • Structured forests for fast edge detection
    • P. Dollar and C. Zitnick. Structured forests for fast edge detection. In ICCV, 2013.
    • (2013) ICCV
    • Dollar, P.1    Zitnick, C.2
  • 9
    • 78149308041 scopus 로고    scopus 로고
    • Category independent object proposals
    • I. Endres and D. Hoiem. Category independent object proposals. In ECCV, pages 575-588, 2010.
    • (2010) ECCV , pp. 575-588
    • Endres, I.1    Hoiem, D.2
  • 10
    • 51949101231 scopus 로고    scopus 로고
    • A discriminatively trained, multiscale, deformable part model
    • P. F. Felzenszwalb, D. A. McAllester, and D. Ramanan. A discriminatively trained, multiscale, deformable part model. In CVPR, 2008.
    • (2008) CVPR
    • Felzenszwalb, P.F.1    McAllester, D.A.2    Ramanan, D.3
  • 13
    • 0035470889 scopus 로고    scopus 로고
    • Greedy function approximation: A gradient boosting machine
    • J. Friedman. Greedy function approximation: A gradient boosting machine. Annals of Statistics, 29:1189-1232, 2001.
    • (2001) Annals of Statistics , vol.29 , pp. 1189-1232
    • Friedman, J.1
  • 14
  • 15
    • 0024090156 scopus 로고
    • A new approach to the maximum-flow problem
    • A. V. Goldberg and R. E. Tarjan. A new approach to the maximum-flow problem. Journal of the ACM (JACM), 35(4):921-940, 1988.
    • (1988) Journal of the ACM (JACM) , vol.35 , Issue.4 , pp. 921-940
    • Goldberg, A.V.1    Tarjan, R.E.2
  • 17
    • 53149130323 scopus 로고    scopus 로고
    • The pseudoflow algorithm: A new algorithm for the maximum-flow problem
    • D. S. Hochbaum. The pseudoflow algorithm: A new algorithm for the maximum-flow problem. Operations research, 56(4):992-1009, 2008.
    • (2008) Operations Research , vol.56 , Issue.4 , pp. 992-1009
    • Hochbaum, D.S.1
  • 18
    • 50649107653 scopus 로고    scopus 로고
    • Recovering occlusion boundaries from a single image
    • D. Hoiem, A. S. Stein, A. A. Efros, and M. Hebert. Recovering occlusion boundaries from a single image. In ICCV, 2007.
    • (2007) ICCV
    • Hoiem, D.1    Stein, A.S.2    Efros, A.A.3    Hebert, M.4
  • 19
    • 84887362370 scopus 로고    scopus 로고
    • Shape sharing for object segmentation
    • J. Kim and K. Grauman. Shape sharing for object segmentation. In ECCV, 2012.
    • (2012) ECCV
    • Kim, J.1    Grauman, K.2
  • 20
    • 36249013608 scopus 로고    scopus 로고
    • Dynamic graph cuts for efficient inference in markov random fields
    • P. Kohli and P. H. Torr. Dynamic graph cuts for efficient inference in markov random fields. PAMI, 29(12):2079-2088, 2007.
    • (2007) PAMI , vol.29 , Issue.12 , pp. 2079-2088
    • Kohli, P.1    Torr, P.H.2
  • 21
    • 50649122028 scopus 로고    scopus 로고
    • Applications of parametric maxflow in computer vision
    • V. Kolmogorov, Y. Boykov, and C. Rother. Applications of parametric maxflow in computer vision. In ICCV, 2007.
    • (2007) ICCV
    • Kolmogorov, V.1    Boykov, Y.2    Rother, C.3
  • 22
    • 0742286180 scopus 로고    scopus 로고
    • What energy functions can be minimized via graph cuts?
    • V. Kolmogorov and R. Zabih. What energy functions can be minimized via graph cuts? PAMI, 26:147-159, 2004.
    • (2004) PAMI , vol.26 , pp. 147-159
    • Kolmogorov, V.1    Zabih, R.2
  • 23
    • 51949099868 scopus 로고    scopus 로고
    • Beyond sliding windows: Object localization by efficient subwindow search
    • C. Lampert, M. Blaschko, and T. Hofmann. Beyond sliding windows: Object localization by efficient subwindow search. In CVPR, 2008.
    • (2008) CVPR
    • Lampert, C.1    Blaschko, M.2    Hofmann, T.3
  • 24
    • 84863045576 scopus 로고    scopus 로고
    • Key-segments for video object segmentation
    • Y. J. Lee, J. Kim, and K. Grauman. Key-segments for video object segmentation. In ICCV, 2011.
    • (2011) ICCV
    • Lee, Y.J.1    Kim, J.2    Grauman, K.3
  • 25
    • 84887362365 scopus 로고    scopus 로고
    • Efficient closed-form solution to generalized boundary detection
    • M. Leordeanu, R. Sukthankar, and C. Sminchisescu. Efficient closed-form solution to generalized boundary detection. In ECCV, 2012.
    • (2012) ECCV
    • Leordeanu, M.1    Sukthankar, R.2    Sminchisescu, C.3
  • 26
    • 78149307307 scopus 로고    scopus 로고
    • Optimal contour closure by superpixel grouping
    • A. Levinshtein, C. Sminchisescu, and S. Dickinson. Optimal contour closure by superpixel grouping. In ECCV, pages 480-493, 2010.
    • (2010) ECCV , pp. 480-493
    • Levinshtein, A.1    Sminchisescu, C.2    Dickinson, S.3
  • 27
    • 77955990360 scopus 로고    scopus 로고
    • Object recognition as ranking holistic figure-ground hypotheses
    • F. Li, J. Carreira, and C. Sminchisescu. Object recognition as ranking holistic figure-ground hypotheses. In CVPR, 2010.
    • (2010) CVPR
    • Li, F.1    Carreira, J.2    Sminchisescu, C.3
  • 28
    • 84887354170 scopus 로고    scopus 로고
    • Sketch tokens: A learned mid-level representation for contour and object detection
    • J. Lim, C. Zitnick, and P. Dollar. Sketch tokens: A learned mid-level representation for contour and object detection. In CVPR, 2013.
    • (2013) CVPR
    • Lim, J.1    Zitnick, C.2    Dollar, P.3
  • 29
    • 84898939584 scopus 로고    scopus 로고
    • Fast template evaluation with vector quantization
    • M. A. Sadeghi and D. Forsyth. Fast template evaluation with vector quantization. In NIPS, pages 2949-2957, 2013.
    • (2013) NIPS , pp. 2949-2957
    • Sadeghi, M.A.1    Forsyth, D.2
  • 30
    • 0034244751 scopus 로고    scopus 로고
    • Normalized cuts and image segmentation
    • J. Shi and J. Malik. Normalized cuts and image segmentation. PAMI, 22(8):888-905, 2000.
    • (2000) PAMI , vol.22 , Issue.8 , pp. 888-905
    • Shi, J.1    Malik, J.2
  • 31
  • 32
    • 84898428842 scopus 로고    scopus 로고
    • Maxflow revisited: An empirical comparison of maxflow algorithms for dense vision problems
    • T. Verma and D. Batra. Maxflow revisited: An empirical comparison of maxflow algorithms for dense vision problems. In BMVC, 2012.
    • (2012) BMVC
    • Verma, T.1    Batra, D.2
  • 33
    • 0038043441 scopus 로고    scopus 로고
    • Image segmentation with ratio cut
    • S. Wang and J. Siskind. Image segmentation with ratio cut. PAMI, 25(6):675-690, 2003.
    • (2003) PAMI , vol.25 , Issue.6 , pp. 675-690
    • Wang, S.1    Siskind, J.2
  • 34
    • 84887330061 scopus 로고    scopus 로고
    • Scalpel: Segmentation cascasdes with localized priors and efficient learning
    • D. Weiss and B. Taskar. Scalpel: Segmentation cascasdes with localized priors and efficient learning. In CVPR, 2013.
    • (2013) CVPR
    • Weiss, D.1    Taskar, B.2
  • 35
    • 0027697605 scopus 로고
    • An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation
    • Z. Wu and R. Leahy. An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation. PAMI, 15(11):1101-1113, 1993.
    • (1993) PAMI , vol.15 , Issue.11 , pp. 1101-1113
    • Wu, Z.1    Leahy, R.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.