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Convolutional neural networks (CNNs) have recently been very successful in a variety of computer vision tasks, especially on those linked to recognition.
Determining optical flow
B. K. P. Horn and B. G. Schunck · 1981
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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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Learning parameterized models of image motion
M. J. Black, Y. Yacoob, A. D. Jepson, and D. J. Fleet · 1997
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Dense estimation and object-based segmentation of the optical flow with robust techniques
E. Mémin and P. Pérez · 1998
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High accuracy optical flow estimation based on a theory for warping
T. Brox, A. Bruhn, N. Papenberg, and J. Weickert · 2004
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im2gps: estimating geographic information from a single image
J. Hays and A. A. Efros · 2008
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Learning optical flow
D. Sun, S. Roth, J. Lewis, and M. J. Black · 2008
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A database and evaluation methodology for optical flow
S. Baker, D. Scharstein, J. Lewis, S. Roth, M. J. Black, and R. Szeliski · 2009
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Structure- and motion-adaptive regularization for high accuracy optic flow
A. Wedel, D. Cremers, T. Pock, and H. Bischof · 2009
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Convolutional learning of spatio-temporal features
G. W. Taylor, R. Fergus, Y. LeCun, and C. Bregler · 2010
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Large displacement optical flow: descriptor matching in variational motion estimation
T. Brox and J. Malik · 2011
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Adaptive deconvolutional networks for mid and high level feature learning
M. D. Zeiler, G. W. Taylor, and R. Fergus · 2011
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A naturalistic open source movie for optical flow evaluation
D. J. Butler, J. Wulff, G. B. Stanley, and M. J. Black · 2012
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Deep neural networks segment neuronal membranes in electron microscopy images
D. C. Ciresan, L. M. Gambardella, A. Giusti, and J. Schmidhuber · 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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Efficient closed-form solution to generalized boundary detection
M. Leordeanu, R. Sukthankar, and C. Sminchisescu · 2012
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Learning hierarchical features for scene labeling
C. Farabet, C. Couprie, L. Najman, and Y. LeCun · 2013
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Vision meets robotics: The kitti dataset
A. Geiger, P. Lenz, C. Stiller, and R. Urtasun · 2013
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Unsupervised learning of depth and motion
K. R. Konda and R. Memisevic · 2013
Descriptor matching with convolutional neural networks: a comparison to SIFT
P. Fischer, A. Dosovitskiy, and T. Brox · 2014
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Rich feature hierarchies for accurate object detection and semantic segmentation
R. Girshick, J. Donahue, T. Darrell, and J. Malik · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 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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Computing the stereo matching cost with a convolutional neural network
J. Zbontar and Y. LeCun · 2014
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Cited alongside, same era.
Locally affine sparse-to-dense matching for motion and occlusion estimation
M. Leordeanu, A. Zanfir, and C. Sminchisescu · 2013
Cited alongside, same era.
Learning the local statistics of optical flow
D. Rosenbaum, D. Zoran, and Y. Weiss · 2013
Cited alongside, same era.
DeepFlow: Large displacement optical flow with deep matching
P. Weinzaepfel, J. Revaud, Z. Harchaoui, and C. Schmid · 2013
Cited alongside, same era.
Seeing 3d chairs: exemplar part-based 2d-3d alignment using a large dataset of cad models
M. Aubry, D. Maturana, A. Efros, B. Russell, and J. Sivic · 2014
Cited alongside, same era.
Fast edge-preserving patchmatch for large displacement optical flow
L. Bao, Q. Yang, and H. Jin · 2014
Cited alongside, same era.
Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
Cited alongside, same era.
Later among the works it cites.
Visualizing and understanding convolutional networks
M. D. Zeiler and R. Fergus · 2014
Later among the works it cites.
Learning to generate chairs with convolutional neural networks
A. Dosovitskiy, J. T. Springenberg, and T. Brox · 2015
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Hypercolumns for object segmentation and fine-grained localization
B. Hariharan, P. Arbeláez, R. Girshick, and J. Malik · 2015
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Optical flow with geometric occlusion estimation and fusion of multiple frames
R. Kennedy and C. Taylor · 2015
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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Fully convolutional networks for semantic segmentation
J. Long, E. Shelhamer, and T. Darrell · 2015
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EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow
J. Revaud, P. Weinzaepfel, Z. Harchaoui, and C. Schmid · 2015
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