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Semantic segmentation has recently witnessed major progress, where fully convolutional neural networks have shown to perform well.
Learning long-term dependencies with gradient descent is difficult
Y. Bengio, P. Simard, and P. Frasconi · 1994
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Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
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Label propagation in video sequences
V. Badrinarayanan, F. Galasso, and R. Cipolla · 2010
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Theano: new features and speed improvements
F. Bastien, P. Lamblin, R. Pascanu, J. Bergstra, I. J. Goodfellow, A. Bergeron, N. Bouchard, and Y. Bengio · 2012
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Changedetection. net: A new change detection benchmark dataset
N. Goyette, P.-M. Jodoin, F. Porikli, J. Konrad, and P. Ishwar · 2012
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Revisiting recurrent neural networks for robust asr
O. Vinyals, S. V. Ravuri, and D. Povey · 2012
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Adadelta: an adaptive learning rate method
M. D. Zeiler · 2012
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Video segmentation by tracking many figure-ground segments
F. Li, T. Kim, A. Humayun, D. Tsai, and J. M. Rehg · 2013
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Understanding high-level semantics by modeling traffic patterns
H. Zhang, A. Geiger, and R. Urtasun · 2013
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On the properties of neural machine translation: Encoder-decoder approaches
K. Cho, B. van Merriënboer, D. Bahdanau, and Y. Bengio · 2014
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Empirical evaluation of gated recurrent neural networks on sequence modeling
J. Chung, C. Gulcehre, K. Cho, and Y. Bengio · 2014
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Seamseg: Video object segmentation using patch seams
S. A. Ramakanth and R. V. Babu · 2014
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Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
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Delving deeper into convolutional networks for learning video representations
N. Ballas, L. Yao, C. Pal, and A. Courville · 2015
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Long-term recurrent convolutional networks for visual recognition and description
J. Donahue, L. Anne Hendricks, S. Guadarrama, M. Rohrbach, S. Venugopalan, K. Saenko, and T. Darrell · 2015
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Learning deconvolution network for semantic segmentation
H. Noh, S. Hong, and B. Han · 2015
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Recurrent convolutional neural networks for object-class segmentation of rgb-d video
M. S. Pavel, H. Schulz, and S. Behnke · 2015
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Fully connected object proposals for video segmentation
F. Perazzi, O. Wang, M. Gross, and A. Sorkine-Hornung · 2015
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Incremental dense semantic stereo fusion for large-scale semantic scene reconstruction
V. Vineet, O. Miksik, M. Lidegaard, M. Nießner, S. Golodetz, V. A. Prisacariu, O. Kähler, D. W. Murray, S. Izadi, P. Perez, and P. H. S. Torr · 2015
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Reseg: A recurrent neural network for object segmentation
F. Visin, K. Kastner, A. Courville, Y. Bengio, M. Matteucci, and K. Cho · 2015
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Densecap: Fully convolutional localization networks for dense captioning
J. Johnson, A. Karpathy, and L. Fei-Fei · 2015
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Efficient piecewise training of deep structured models for semantic segmentation
G. Lin, C. Shen, I. Reid, et al · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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The semantic paintbrush: Interactive 3d mapping and recognition in large outdoor spaces
O. Miksik, V. Vineet, M. Lidegaard, R. Prasaath, M. Nießner, S. Golodetz, S. L. Hicks, P. Pérez, S. Izadi, and P. H. Torr · 2015
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A benchmark dataset and evaluation methodology for video object segmentation
F. Perazzi, J. P.-T. B. McWilliams, L. Van Gool, M. Gross, and A. Sorkine-Hornung
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S. Zheng, S. Jayasumana, B. Romera-Paredes, V. Vineet, Z. Su, D. Du, C. Huang, and P. H. Torr · 2015
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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
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The synthia dataset: A large collection of synthetic images for semantic segmentation of urban scenes
G. Ros, L. Sellart, J. Materzynska, D. Vazquez, and A. M. Lopez · 2016
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Enhancing semantic segmentation for robotics: The power of 3-d entangled forests
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