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We propose an approach to semantic (image) segmentation that reduces the computational costs by a factor of 25 with limited impact on the quality of results.
A practical guide to training restricted boltzmann machines
G. Hinton · 2010
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ImageNet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. Hinton · 2012
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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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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Segnet: A deep convolutional encoder-decoder architecture for image segmentation
V. Badrinarayanan, A. Kendall, and R. Cipolla · 2015
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Semantic image segmentation with deep convolutional nets and fully connected CRFs
L. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. Yuille · 2015
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Attention to scale: Scale-aware semantic image segmentation
L.-C. Chen, Y. Yang, J. Wang, W. Xu, and A. L. Yuille · 2015
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MXNet: A flexible and efficient machine learning library for heterogeneous distributed systems
T. Chen, M. Li, Y. Li, M. Lin, N. Wang, M. Wang, T. Xiao, B. Xu, C. Zhang, and Z. Zhang · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
Cited alongside, same era.
L.-C. Chen, G. Papandreou, I. Kokkinos, K. Murphy, and A. L. Yuille · 2016
Cited alongside, same era.
The Cityscapes dataset for semantic urban scene understanding
M. Cordts, M. Omran, S. Ramos, T. Rehfeld, M. Enzweiler, R. Benenson, U. Franke, S. Roth, and B. Schiele · 2016
Cited alongside, same era.
Instance-aware semantic segmentation via multi-task network cascades
J. Dai, K. He, and J. Sun · 2016
Cited alongside, same era.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Learning to refine object segments
P. O. Pinheiro, T.-Y. Lin, R. Collobert, and P. Dollàr · 2016
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Residual networks behave like ensembles of relatively shallow networks
A. Veit, M. Wilber, and S. Belongie · 2016
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Bridging category-level and instance-level semantic image segmentation
Z. Wu, C. Shen, and A. van den Hengel · 2016
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H. Zhao, J. Shi, X. Qi, X. Wang, and J. Jia · 2016
Later among the works it cites.
Highway and residual networks learn unrolled iterative estimation. international conference on learning representations
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K. He, X. Zhang, S. Ren, and J. Sun · 2016
Cited alongside, same era.
Refinenet: Multi-path refinement networks for high-resolution semantic segmentation
G. Lin, A. Milan, C. Shen, and I. Reid · 2016
Cited alongside, same era.
Enet: A deep neural network architecture for real-time semantic segmentation
A. Paszke, A. Chaurasia, S. Kim, and E. Culurciello · 2016
Cited alongside, same era.
K. Greff, R. K. Srivastava, and J. Schmidhuber · 2017
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Supervised deep sparse coding networks
X. Sun, N. M. Nasrabadi, and T. D. Tran · 2017
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Icnet for real-time semantic segmentation on high-resolution images
H. Zhao, X. Qi, X. Shen, J. Shi, and J. Jia · 2017
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