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Existing works on single-image 3D reconstruction mainly focus on shape recovery.
Long short-term memory
S. Hochreiter and J. Schmidhuber · 1997
Earlier work this paper cites.
An accurate method for voxelizing polygon meshes
J. Huang, R. Yagel, V. Filippov, and Y. Kurzion · 1998
Earlier work this paper cites.
A fast learning algorithm for deep belief nets
G. E. Hinton and S. Osindero · 2006
Earlier work this paper cites.
Very deep convolutional networks for large-scale image recognition
K. Simonyan and A. Zisserman · 2014
Earlier work this paper cites.
Detailed full-body reconstructions of moving people from monocular RGB-D sequences
F. Bogo, M. J. Black, M. Loper, and J. Romero · 2015
Earlier work this paper cites.
Shapenet: An information-rich 3d model repository
A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, et al · 2015
Earlier work this paper cites.
Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Earlier work this paper cites.
Smpl: A skinned multi-person linear model
M. Loper, N. Mahmood, J. Romero, G. Pons-Moll, and M. J. Black · 2015
Cited alongside, same era.
Dyna: A model of dynamic human shape in motion
G. Pons-Moll, J. Romero, N. Mahmood, and M. J. Black · 2015
Cited alongside, same era.
3d shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Cited alongside, same era.
3d-r2n2: A unified approach for single and multi-view 3d object reconstruction
C. B. Choy, D. Xu, J. Gwak, K. Chen, and S. Savarese · 2016
Cited alongside, same era.
Multi-view 3d models from single images with a convolutional network
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2016
Cited alongside, same era.
Training deep neural networks on imbalanced data sets
S. Wang, W. Liu, J. Wu, L. Cao, Q. Meng, and P. J. Kennedy · 2016
Cited alongside, same era.
Spatiotemporal deformable prototypes for motion anomaly detection
R. Bensch, N. Scherf, J. Huisken, T. Brox, and O. Ronneberger · 2017
Later among the works it cites.
Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration
Y. Chen and T. Pock · 2017
Later among the works it cites.
MarrNet: 3D Shape Reconstruction via 2.5D Sketches
J. Wu, Y. Wang, T. Xue, X. Sun, W. T. Freeman, and J. B. Tenenbaum · 2017
Later among the works it cites.
Large-scale 3d shape reconstruction and segmentation from shapenet core55
L. Yi, H. Su, L. Shao, M. Savva, H. Huang, Y. Zhou, B. Graham, M. Engelcke, R. Klokov, V. Lempitsky, et al · 2017
Later among the works it cites.
Detailed, accurate, human shape estimation from clothed 3d scan sequences
C. Zhang, S. Pujades, M. Black, and G. Pons-Moll · 2017
Later among the works it cites.
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View synthesis by appearance flow
T. Zhou, S. Tulsiani, W. Sun, J. Malik, and A. A. Efros · 2016
Cited alongside, same era.
Rethinking reprojection: Closing the loop for pose-aware shape reconstruction from a single image
R. Zhu, H. K. Galoogahi, C. Wang, and S. Lucey · 2017
Later among the works it cites.
Multi-view consistency as supervisory signal for learning shape and pose prediction
S. Tulsiani, A. A. Efros, and J. Malik · 2018
Closest in time.