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Learning based methods have shown very promising results for the task of depth estimation in single images.
Photometric method for determining surface orientation from multiple images
R. J. Woodham · 1980
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A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
D. Scharstein and R. Szeliski · 2002
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Multiple view geometry in computer vision
R. Hartley and A. Zisserman · 2003
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Image quality assessment: from error visibility to structural similarity
Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simoncelli · 2004
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Automatic photo pop-up
D. Hoiem, A. A. Efros, and M. Hebert · 2005
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Recovering occlusion boundaries from a single image
D. Hoiem, A. N. Stein, A. A. Efros, and M. Hebert · 2007
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Semantic object classes in video: A high-definition ground truth database
G. J. Brostow, J. Fauqueur, and R. Cipolla · 2009
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Make3d: Learning 3d scene structure from a single still image
A. Saxena, M. Sun, and A. Y. Ng · 2009
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Rectified linear units improve restricted boltzmann machines
V. Nair and G. E. Hinton · 2010
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Real-time stereo reconstruction in robotically assisted minimally invasive surgery
D. Stoyanov, M. V. Scarzanella, P. Pratt, and G.-Z. Yang · 2010
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Learning to Find Occlusion Regions
A. Humayun, O. Mac Aodha, and G. J. Brostow · 2011
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Heliometric stereo: Shape from sun position
A. Abrams, C. Hawley, and R. Pless · 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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Perceiving in depth, volume 1: basic mechanisms
I. P. Howard · 2012
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Indoor segmentation and support inference from rgbd images
P. K. Nathan Silberman, Derek Hoiem and R. Fergus · 2012
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Pm-huber: Patchmatch with huber regularization for stereo matching
P. Heise, S. Klose, B. Jensen, and A. Knoll · 2013
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Real-time human pose recognition in parts from single depth images
J. Shotton, T. Sharp, A. Kipman, A. Fitzgibbon, M. Finocchio, A. Blake, M. Cook, and R. Moore · 2013
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Depth map prediction from a single image using a multi-scale deep network
D. Eigen, C. Puhrsch, and R. Fergus · 2014
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Depth transfer: Depth extraction from video using non-parametric sampling
K. Karsch, C. Liu, and S. B. Kang · 2014
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Automatic scene inference for 3d object compositing
K. Karsch, K. Sunkavalli, S. Hadap, N. Carr, H. Jin, R. Fonte, M. Sittig, and D. Forsyth · 2014
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2014
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Pulling things out of perspective
L. Ladickỳ, J. Shi, and M. Pollefeys · 2014
Cited alongside, same era.
Discrete-continuous depth estimation from a single image
M. Liu, M. Salzmann, and X. He · 2014
Cited alongside, same era.
Fast bilateral-space stereo for synthetic defocus
J. T. Barron, A. Adams, Y. Shih, and C. Hernández · 2015
Cited alongside, same era.
Fast and accurate deep network learning by exponential linear units (elus)
D.-A. Clevert, T. Unterthiner, and S. Hochreiter · 2015
Cited alongside, same era.
Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
Tensorflow: Large-scale machine learning on heterogeneous distributed systems
M. Abadi, A. Agarwal, P. Barham, E. Brevdo, Z. Chen, C. Citro, G. S. Corrado, A. Davis, J. Dean, M. Devin, et al · 2016
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Y. Cao, Z. Wu, and C. Shen · 2016
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Single-image depth perception in the wild
W. Chen, Z. Fu, D. Yang, and J. Deng · 2016
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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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Structured Prediction of Unobserved Voxels From a Single Depth Image
M. Firman, O. Mac Aodha, S. Julier, and G. J. Brostow · 2016
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D. Eigen and R. Fergus · 2015
Cited alongside, same era.
Flownet: Learning optical flow with convolutional networks
P. Fischer, A. Dosovitskiy, E. Ilg, P. Häusser, C. Hazırbaş, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox · 2015
Cited alongside, same era.
Multi-view stereo: A tutorial
Y. Furukawa and C. Hernández · 2015
Cited alongside, same era.
Multi-view reconstruction of highly specular surfaces in uncontrolled environments
C. Godard, P. Hedman, W. Li, and G. J. Brostow · 2015
Cited alongside, same era.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Cited alongside, same era.
Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and K. Kavukcuoglu · 2015
Cited alongside, same era.
Learning the matching function
L. Ladickỳ, C. Häne, and M. Pollefeys · 2015
Cited alongside, same era.
Deepstereo: Learning to predict new views from the world’s imagery
J. Flynn, I. Neulander, J. Philbin, and N. Snavely · 2016
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Virtual worlds as proxy for multi-object tracking analysis
A. Gaidon, Q. Wang, Y. Cabon, and E. Vig · 2016
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Unsupervised CNN for single view depth estimation: Geometry to the rescue
R. Garg, V. Kumar BG, and I. Reid · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Deeper depth prediction with fully convolutional residual networks
I. Laina, C. Rupprecht, V. Belagiannis, F. Tombari, and N. Navab · 2016
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Efficient deep learning for stereo matching
W. Luo, A. Schwing, and R. Urtasun · 2016
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A large dataset to train convolutional networks for disparity, optical flow, and scene flow estimation
N. Mayer, E. Ilg, P. Häusser, P. Fischer, D. Cremers, A. Dosovitskiy, and T. Brox · 2016
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Deconvolution and checkerboard artifacts
A. Odena, V. Dumoulin, and C. Olah · 2016
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Dense monocular depth estimation in complex dynamic scenes
R. Ranftl, V. Vineet, Q. Chen, and V. Koltun · 2016
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Fully convolutional networks for semantic segmentation
E. Shelhamer, J. Long, and T. Darrell · 2016
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Deep3d: Fully automatic 2d-to-3d video conversion with deep convolutional neural networks
J. Xie, R. Girshick, and A. Farhadi · 2016
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Stereo matching by training a convolutional neural network to compare image patches
J. Žbontar and Y. LeCun · 2016
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Learning dense correspondence via 3d-guided cycle consistency
T. Zhou, P. Krähenbühl, M. Aubry, Q. Huang, and A. A. Efros · 2016
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View synthesis by appearance flow
T. Zhou, S. Tulsiani, W. Sun, J. Malik, and A. A. Efros · 2016
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