[1] |
LAFFERTY J , MCCALLUM A , PEREIRAF C , et al. Conditional random fields:probabilistic models for segmenting and labeling sequence data [C]// ICML,June 28-July 1,2001,Williams College,UK. New Jersey: IEEE Press, 2001.
|
[2] |
BORENSTEIN E , SHARON E , ULLMAN S , et al. Combining top-down and bottom-up segmentation [C]//Conference on Computer Vision and Pattern Recognition,June 27-July 2,2004,Washington,DC,USA. New Jersey: IEEE Press, 2004.
|
[3] |
HE X , ZEMEL R S , CARREIRAPERPINAN M A , et al. Multi-scale conditional random fields for image labeling[C]//Conference on Computer Vision and Pattern Recognition,June 27-July 2,2004,Washington,DC,USA. New Jersey: IEEE Press, 2004.
|
[4] |
HE X , ZEMEL R S , RAY D , et al. Learning and incorporating top-down cues in image segmentation[C]// European Conference on Computer Vision,May 7-13,2006,Graz,Austria. New Jersey: IEEE Press, 2006:338-351.
|
[5] |
SHOTTON J , WINN J , ROTHER C , et al. Texton boost for image understanding:multi-class object recognition and segmentation by jointly modeling texture,layout,and context[J]. International Journal of Computer Vision, 2009,81(1):2-23.
|
[6] |
ZHANG L . A unified probabilistic graphical model and its application to image segmentation[J]. Rensselaer Polytechnic Institute, 2009(3).
|
[7] |
SMOLENSKY P . Information processing in dynamical systems:foundations of harmony theory[M]. Cambride: MIT Press, 1986(1):194-281.
|
[8] |
SALAKHUTDINOV R , HINTON G E . Deep Boltzmann machines[J]. Journal of Machine Learning Research, 2009,5(2):1967-2006.
|
[9] |
ESLAMI S M , HEESS N , WILLIAMS C K , et al. The shape Boltzmann machine:a strong model of object shape[J]. International Journal of Computer Vision, 2014,107(2):155-176.
|
[10] |
KAE A , SOHN K , LEE H , et al. Augmenting CRFs with Boltzmann machine shape priors for image labeling [C]//Conference on Computer Vision and Pattern Recognition,June 23-28,2013,Portland,Oregon,USA. New Jersey: IEEE Press, 2013.
|
[11] |
KAE A , MARLIN B M , LEARNEDMILLER E G , et al. The shape-time random field for semantic video labeling [C]//Conference on Computer Vision and Pattern Recognition,June 23-28,2014,Columbus,OH,USA. New Jersey: IEEE Press, 2014.
|
[12] |
CHEN F , YU H , HU R , et al. Deep learning shape priors for object segmentation [C]//Conference on Computer Vision and Pattern Recognition,June 23-28,2013,Portland,Oregon,USA. New Jersey: IEEE Press, 2013.
|
[13] |
CREMERS D , SCHMIDT F R , BARTHEL F , et al. Shape priors in variational image segmentation:Convexity,Lipschitz continuity and globally optimal solutions [C]//Conference on Computer Vision and Pattern Recognition,June 24-26,2008,Anchorage,Alaska,USA. New Jersey: IEEE Press, 2008.
|
[14] |
ARBELAEZ P , HARIHARAN B , GU C , et al. Semantic segmentation using regions and parts [C]//Conference on Computer Vision and Pattern Recognition,June 16-21,2012,Providence,RI,USA. New Jersey: IEEE Press, 2012.
|
[15] |
MURPHY K , WEISS Y , JORDAN M I , et al. Loopy beliefpropagation for approximate inference:an empirical study[C]//15th Conference on Uncertainty in Artificial Intelligence,July 30-August 1,1999,Stockholm,Sweden. New Jersey: IEEE Press, 1999.
|
[16] |
SCHMIDT M . minFunc:unconstrained differentiable multivariate optimization in Matlab[EB/OL]. 2016-07-10.
|
[17] |
SAUL L K , JAAKKOLA T S , JORDAN M I , et al. Mean field theory for sigmoid belief networks[J]. Journal of Artificial Intelligence Research, 1996(13).
|
[18] |
MNIH V , LAROCHELLE H , HINTON G E , et al. Conditional restricted Boltzmann machines for structured output prediction[C]//Conference on Uncertainty in Artificial Intelligence,Aug 15-17,2012,Catalina Island,USA. New Jersey: IEEE Press, 2012.
|
[19] |
WANG L , SHI J , SONG G , et al. Object detection combining recognition and segmentation[C]//Asian Conference on Computer Vision,November 18-22,2007,Tokyo,Japan. New Jersey: IEEE Press, 2007.
|
[20] |
WELINDER P , BRANSON S , MITA T , et al. Caltech-UCSD Birds 200[J]. California Institute of Technology, 2010.
|
[21] |
YANG J , SAFAR S , YANG M H . Max-margin Boltzmann machines for object segmentation [C]//IEEE Conference on Computer Vision and Pattern Recognition,June 23-28,2014,Columbus,OH,USA. New Jersey: IEEE Press, 2014.
|
[22] |
ACHANTA R P , SHAJI A , SMITH K M , et al. SLIC superpixels compared to state-of-the-art superpixelmethods[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012,34(11):2274-2282.
|
[23] |
MALIK J , BELONGIE S , SHI J , et al. Textons,contours and regions:cue integration in image segmentation [C]//ICCV,September 20-25,1999,Kerkyra,Corfu,Greece. New Jersey: IEEE Press, 1999.
|
[24] |
MARTIN D R , FOWLKES C C , MALIK J , et al. Learning to detect natural image boundaries using brightness and texture[C]//Conference on Neural Information Processing Systems,December 8-13,2003,Providence,USA. New Jersey: IEEE Press, 2003.
|
[25] |
HUANG G B , NARAYANA M , LEARNEDMILLER E G , et al. Towards unconstrained face recognition [C]//Conference on Computer Vision and Pattern Recognition,June 24-26,2008,Anchorage,Alaska,USA. New Jersey: IEEE Press, 2008.
|
[26] |
COHN T . Efficient inference in large conditional random Fields[M]. Berlin: Springer, 2006:606-613.
|