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The topic of semantic segmentation has witnessed considerable progress due to the powerful features learned by convolutional neural networks (CNNs).
Backpropagation applied to handwritten zip code recognition
Y. LeCun, B. Boser, J. S. Denker, D. Henderson, R. E. Howard, W. Hubbard, and L. D. Jackel · 1989
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Matching pursuits with time-frequency dictionaries
S. G. Mallat and Z. Zhang · 1993
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Textonboost: Joint appearance, shape and context modeling for mulit-class object recognition and segmentation
J. Shotton, J. Winn, C. Rother, and A. Criminisi · 2006
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Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
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The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
Earlier work this paper cites.
Superparsing: scalable nonparametric image parsing with superpixels
J. Tighe and S. Lazebnik · 2010
Earlier work this paper cites.
Learning active basis model for object detection and recognition
Y. N. Wu, Z. Si, H. Gong, and S.-C. Zhu · 2010
Earlier work this paper cites.
Layered object detection for multi-class segmentation
Y. Yang, S. Hallman, D. Ramanan, and C. Fowlkes · 2010
Earlier work this paper cites.
Object segmentation by alignment of poselet activations to image contours
T. Brox, L. Bourdev, S. Maji, and J. Malik · 2011
Cited alongside, same era.
Learning photographic global tonal adjustment with a database of input / output image pairs
V. Bychkovsky, S. Paris, E. Chan, and F. Durand · 2011
Cited alongside, same era.
Semantic contours from inverse detectors
B. Hariharan, P. Arbeláez, L. Bourdev, S. Maji, and J. Malik · 2011
Cited alongside, same era.
Semantic segmentation with second-order pooling
J. Carreira, R. Caseiro, J. Batista, and C. Sminchisescu · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
Decaf: A deep convolutional activation feature for generic visual recognition
Visualizing and understanding convolutional neural networks
M. D. Zeiler and R. Fergus · 2013
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Multiscale combinatorial grouping
P. Arbeláez, J. Pont-Tuset, J. T. Barron, F. Marques, 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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Spatial pyramid pooling in deep convolutional networks for visual recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2014
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Caffe: Convolutional architecture for fast feature embedding
Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
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J. Donahue, Y. Jia, O. Vinyals, J. Hoffman, N. Zhang, E. Tzeng, and T. Darrell · 2013
Cited alongside, same era.
Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2013
Cited alongside, same era.
Selective search for object recognition
J. R. Uijlings, K. E. van de Sande, T. Gevers, and A. W. Smeulders · 2013
Cited alongside, same era.
J. Long, E. Shelhamer, and T. Darrell · 2014
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The role of context for object detection and semantic segmentation in the wild
R. Mottaghi, X. Chen, X. Liu, N.-G. Cho, S.-W. Lee, S. Fidler, R. Urtasun, and A. Yuille · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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