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The representation of geometry in real-time 3D perception systems continues to be a critical research issue.
Learning internal representations by error propagation
D. E. Rumelhart, G. E. Hinton, and R. J. Williams · 1986
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Real-Time Simultaneous Localisation and Mapping with a Single Camera
A. J. Davison · 2003
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Simultaneous Localisation and Mapping (SLAM): Part I The Essential Algorithms
H. Durrant-Whyte and T. Bailey · 2006
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Unified Inverse Depth Parametrization for Monocular SLAM
J. M. M. Montiel, J. Civera, and A. J. Davison · 2006
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Parallel Tracking and Mapping for Small AR Workspaces
G. Klein and D. W. Murray · 2007
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DTAM: Dense Tracking and Mapping in Real-Time
R. A. Newcombe, S. Lovegrove, and A. J. Davison · 2011
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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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Robust odometry estimation for RGB-D cameras
C. Kerl, J. Sturm, and D. Cremers · 2013
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SLAM++: Simultaneous Localisation and Mapping at the Level of Objects
R. F. Salas-Moreno, R. A. Newcombe, H. Strasdat, P. H. J. Kelly, and A. J. Davison · 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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LSD-SLAM: Large-scale direct monocular SLAM
J. Engel, T. Schoeps, and D. Cremers · 2014
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Auto-Encoding Variational Bayes
D. P. Kingma and M. Welling · 2014
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Dense planar SLAM
R. F. Salas-Moreno, B. Glocker, P. H. J. Kelly, and A. J. Davison · 2014
Cited alongside, same era.
Simultaneous localization and mapping with infinite planes
M. Kaess · 2015
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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Deep Convolutional Neural Fields for Depth Estimation from a Single Image
F. Liu, C. Shen, and G. Lin · 2015
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ORB-SLAM: a Versatile and Accurate Monocular SLAM System
R. Mur-Artal, J. M. M. Montiel, and J. D. Tardós · 2015
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U-Net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P. Fischer, and T. Brox · 2015
Cited alongside, same era.
VidLoc: A deep spatio-temporal model for 6-dof video-clip relocalization
R. Clark, S. Wang, H. Wen, A. Markham, and N. Trigoni · 2017
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VINet: Visual-inertial odometry as a sequence-to-sequence learning problem
R. Clark, S. Wang, H. Wen, A. Markham, and N. Trigoni · 2017
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Direct sparse odometry
J. Engel, V. Koltun, and D. Cremers · 2017
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What uncertainties do we need in bayesian deep learning for computer vision?
A. Kendall and Y. Gal · 2017
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SceneNet RGB-D: Can 5M synthetic images beat generic ImageNet pre-training on indoor segmentation?
J. McCormac, A. Handa, S. Leutenegger, and A. J. Davison · 2017
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Monocular visual odometry: Sparse joint optimisation or dense alternation?
L. Platinsky, A. J. Davison, and S. Leutenegger · 2017
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A Primer on the Differential Calculus of 3D Orientations
M. Bloesch, H. Sommer, T. Laidlow, M. Burri, G. Nützi, P. Fankhauser, D. Bellicoso, C. Gehring, S. Leutenegger, M. Hutter, and R. Siegwart · 2016
Cited alongside, same era.
The EuRoC Micro Aerial Vehicle Datasets
M. Burri, J. Nikolic, P. Gohl, T. Schneider, J. Rehder, S. Omari, M. W. Achtelik, and R. Siegwart · 2016
Cited alongside, same era.
Multi-modal Auto-Encoders as Joint Estimators for Robotics Scene Understanding
C. Cadena, A. Dick, and I. D. Reid · 2016
Cited alongside, same era.
Unsupervised CNN for single view depth estimation: Geometry to the rescue
R. Garg, V. K. B. G, G. Carneiro, and I. Reid · 2016
Cited alongside, same era.
DeMoN: Depth and motion network for learning monocular stereo
B. Ummenhofer, H. Zhou, J. Uhrig, N. Mayer, E. Ilg, A. Dosovitskiy, and T. Brox · 2016
Cited alongside, same era.
Later among the works it cites.
CNN-SLAM: Real-time dense monocular slam with learned depth prediction
K. Tateno, F. Tombari, I. Laina, and N. Navab · 2017
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DeepVO: Towards end to end visual odometry with deep recurrent convolutional neural networks
S. Wang, R. Clark, H. Wen, and N. Trigoni · 2017
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Dense monocular reconstruction using surface normals
C. S. Weerasekera, Y. Latif, R. Garg, and I. Reid · 2017
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Unsupervised learning of depth and ego-motion from video
T. Zhou, M. Brown, N. Snavely, and D. G. Lowe · 2017
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GeoNet: Unsupervised Learning of Dense Depth, Optical Flow and Camera Pose
Z. Yin and J. Shi · 2018
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