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We introduce a purely feed-forward architecture for semantic segmentation.
Class segmentation and object localization with superpixel neighborhoods
B. Fulkerson, A. Vedaldi, and S. Soatto · 2009
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Associative hierarchical CRFs for object class image segmentation
L. Ladickỳ, C. Russell, P. Kohli, and P. H. S. Torr · 2009
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Context by region ancestry
J. J. Lim, P. Arbeláez, C. Gu, and J. Malik · 2009
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Textonboost for image understanding: Multi-class object recognition and segmentation by jointly modeling texture, layout, and context
J. Shotton, J. Winn, C. Rother, and A. Criminisi · 2009
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Semantic contours from inverse detectors
B. Hariharan, P. Arbelaez, L. Bourdev, S. Maji, and J. Malik · 2011
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Probabilistic joint image segmentation and labeling
A. Ion, J. Carreira, and C. Sminchisescu · 2011
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Pylon model for semantic segmentation
V. Lempitsky, A. Vedaldi, and A. Zisserman · 2011
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Are spatial and global constraints really necessary for segmentation?
A. Lucchi, Y. Li, X. Boix, K. Smith, and P. Fua · 2011
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Parsing Natural Scenes and Natural Language with Recursive Neural Networks
R. Socher, C. C. Lin, A. Y. Ng, and C. D. Manning · 2011
Earlier work this paper cites.
Empirical risk minimization of graphical model parameters given approximate inference, decoding, and model structure
V. Stoyanov, A. Ropson, and J. Eisner · 2011
Earlier work this paper cites.
Slic superpixels compared to state-of-the-art superpixel methods
R. Achanta, A. Shaji, K. Smith, A. Lucchi, P. Fua, and S. Ssstrunk · 2012
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Semantic segmentation using regions and parts
P. Arbelaez, B. Hariharan, C. Gu, S. Gupta, L. Bourdev, and J. Malik · 2012
Earlier work this paper cites.
Harmony potentials - fusing global and local scale for semantic image segmentation
X. Boix, J. M. Gonfaus, J. van de Weijer, A. D. Bagdanov, J. S. Gual, and J. Gonzàlez · 2012
Earlier work this paper cites.
Semantic segmentation with second-order pooling
J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu · 2012
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Object recognition by sequential figure-ground ranking
J. Carreira, F. Li, and C. Sminchisescu · 2012
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Cpmc: Automatic object segmentation using constrained parametric min-cuts
J. Carreira and C. Sminchisescu · 2012
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Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
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Segmentation propagation in imagenet
D. Kuettel, M. Guillaumin, and V. Ferrari · 2012
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Structured output learning with high order loss functions
D. Tarlow and R. S. Zemel · 2012
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Personal communication
M. Cogswell, X. Lin, and D. Batra · 2014
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The pascal visual object classes challenge: A retrospective
M. Everingham, S. Eslami, L. Van Gool, C. Williams, J. Winn, and A. Zisserman · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donohue, T. Darrell, and J. Malik · 2014
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Hypercolumns for object segmentation and fine-grained localization
B. Hariharan, P. A. an R. Girshick, and J. Malik · 2014
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Simultaneous detection and segmentation
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2014
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Caffe: Convolutional architecture for fast feature embedding
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Learning hierarchical features for scene labeling
C. Farabet, C. Couprie, L. Najman, and Y. LeCun · 2013
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Deep and wide multiscale recursive networks for robust image labeling
G. B. Huang and V. Jain · 2013
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Codemaps segment, classify and search objects locally
Z. Li, E. Gavves, K. E. A. van de Sande, C. G. M. Snoek, and A. W. M. Smeulders · 2013
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Selective search for object recognition
J. R. R. Uijlings, K. E. A. van de Sande, T. Gevers, and A. W. M. Smeulders · 2013
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Discriminative re-ranking of diverse segmentations
P. Yadollahpour, D. Batra, and G. Shakhnarovich · 2013
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Return of the devil in the details: Delving deep into convolutional nets
K. Chatfield, K. Simonyan, A. Vedaldi, and A. Zisserman · 2014
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Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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Mean field networks
Y. Li and R. Zemel · 2014
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2014
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A robust multilevel segment description for multi-class object recognition
M. Mostajabi and I. Gholampour · 2014
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Recurrent convolutional neural networks for scene labeling
P. H. O. Pinheiro and R. Collobert · 2014
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Imagenet large scale visual recognition challenge
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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