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We propose a novel deep architecture, SegNet, for semantic pixel wise image labelling.
Gradient-based learning applied to document recognition
Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner · 1998
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Numerical Optimization
J. Nocedal and S. J. Wright · 2006
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Unsupervised learning of invariant feature hierarchies with applications to object recognition
M. Ranzato, F. J. Huang, Y. Boureau, and Y. LeCun · 2007
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Segmentation and recognition using structure from motion point clouds
G. Brostow, J. Shotton, J., and R. Cipolla · 2008
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Nonlinear image representation using divisive normalization
S. Lyu and E. P. Simoncelli · 2008
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Labelme: a database and web-based tool for image annotation
B. C. Russell, A. Torralba, K. P. Murphy, and W. T. Freeman · 2008
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Semantic texton forests for image categorization and segmentation
J. Shotton, M. Johnson, and R. Cipolla · 2008
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Semantic object classes in video: A high-definition ground truth database
G. Brostow, J. Fauqueur, and R. Cipolla · 2009
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Decomposing a scene into geometric and semantically consistent regions
S. Gould, R. Fulton, and D. Koller · 2009
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Deep convolutional networks for scene parsing
D. Grangier, L. Bottou, and R. Collobert · 2009
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What is the best multi-stage architecture for object recognition?
K. Jarrett, K. Kavukcuoglu, M. Ranzato, and Y. LeCun · 2009
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Combining appearance and structure from motion features for road scene understanding
P. Sturgess, K. Alahari, L. Ladicky, and P. H.S.Torr · 2009
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Learning convolutional feature hierarchies for visual recognition
K. Kavukcuoglu, P. Sermanet, Y. Boureau, K. Gregor, M. Mathieu, and Y. LeCun · 2010
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What, where and how many? combining object detectors and crfs
L. Ladicky, P. Sturgess, K. Alahari, C. Russell, and P. H. S. Torr · 2010
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Deconvolutional networks
M. D. Zeiler, D. Krishnan, G. W. Taylor, and R. Fergus · 2010
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Semantic segmentation of urban scenes using dense depth maps
C. Zhang, L. Wang, and R. Yang · 2010
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Efficient inference in fully connected crfs with gaussian edge potentials
V. Koltun · 2011
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Structured class-labels in random forests for semantic image labelling
P. Kontschieder, S. R. Bulo, H. Bischof, and M. Pelillo · 2011
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On optimization methods for deep learning
Q. V. Le, J. Ngiam, A. Coates, A. Lahiri, B. Prochnow, and A. Y. Ng · 2011
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Multimodal deep learning
J. Ngiam, A. Khosla, M. Kim, J. Nam, H. Lee, and A. Y. Ng · 2011
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Parsing natural scenes and natural language with recursive neural networks
R. Socher, C. C. Lin, C. Manning, and A. Y. Ng · 2011
Perceptual organization and recognition of indoor scenes from rgb-d images
S. Gupta, P. Arbelaez, and J. Malik · 2013
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Intriguing properties of neural networks
C. Szegedy, W. Zaremba, I. Sutskever, J. Bruna, D. Erhan, I. Goodfellow, and R. Fergus · 2013
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Superparsing
J. Tighe and S. Lazebnik · 2013
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Neural decision forests for semantic image labelling
S. R. Bulo and P. Kontschieder · 2014
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Learning a deep convolutional network for image super-resolution
C. Dong, C. C. Loy, K. He, and X. Tang · 2014
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Depth map prediction from a single image using a multi-scale deep network
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Scene parsing with multiscale feature learning, purity trees, and optimal covers
C. Farabet, C. Couprie, L. Najman, and Y. LeCun · 2012
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Are we ready for autonomous driving? the KITTI vision benchmark suite
A. Geiger, P. Lenz, and R. Urtasun · 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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Rgb-(d) scene labeling: Features and algorithms
X. Ren, L. Bo, and D. Fox · 2012
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minfunc: unconstrained differentiable multivariate optimization in matlab
M. Schmidt · 2012
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Indoor segmentation and support inference from rgbd images
N. Silberman, D. Hoiem, P. Kohli, and R. Fergus · 2012
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D. Eigen, C. Puhrsch, and R. Fergus · 2014
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Unrolling loopy top-down semantic feedback in convolutional deep networks
C. Gatta, A. Romero, and J. van de Weijer · 2014
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Dense 3D Semantic Mapping of Indoor Scenes from RGB-D Images
A. Hermans, G. Floros, and B. Leibe · 2014
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Fast semantic segmentation of rgb-d scenes with gpu-accelerated deep neural networks
N. Höft, H. Schulz, and S. Behnke · 2014
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Recurrent convolutional neural networks for scene labeling
P. Pinheiro and R. Collobert · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Going deeper with convolutions
C. Szegedy, W. Liu, Y. Jia, P. Sermanet, S. Reed, D. Anguelov, D. Erhan, V. Vanhoucke, and A. Rabinovich · 2014
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Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
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Vision-based offline-online perception paradigm for autonomous driving
G. Ros, S. Ramos, M. Granados, A. Bakhtiary, D. Vazquez, and A. Lopez · 2015
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