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Estimating the 3D shape of an object from a single or multiple images has gained popularity thanks to the recent breakthroughs powered by deep learning.
The interpretation of structure from motion
S. Ullman · 1979
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The visual hull concept for silhouette-based image understanding
A. Laurentini · 1994
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Bundle adjustment—a modern synthesis
B. Triggs, P. F. McLauchlan, R. I. Hartley, and A. W. Fitzgibbon · 1999
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A theory of shape by space carving
K. N. Kutulakos and S. M. Seitz · 2000
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Multiple view geometry in computer vision
R. Hartley and A. Zisserman · 2003
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Unsupervised 3d object recognition and reconstruction in unordered datasets
M. Brown and D. G. Lowe · 2005
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Photo tourism: exploring photo collections in 3d
N. Snavely, S. M. Seitz, and R. Szeliski · 2006
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Parsing ikea objects: Fine pose estimation
J. J. Lim, H. Pirsiavash, and A. Torralba · 2013
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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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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Auto-encoding variational bayes
D. P. Kingma and M. Welling · 2014
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Beyond pascal: A benchmark for 3d object detection in the wild
Y. Xiang, R. Mottaghi, and S. Savarese · 2014
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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
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Visual simultaneous localization and mapping: a survey
J. Fuentes-Pacheco, J. Ruiz-Ascencio, and J. M. Rendón-Mancha · 2015
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Category-specific object reconstruction from a single image
A. Kar, S. Tulsiani, J. Carreira, and J. Malik · 2015
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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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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
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Learning a predictable and generative vector representation for objects
R. Girdhar, D. F. Fouhey, M. Rodriguez, and A. Gupta · 2016
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Unsupervised learning of 3d structure from images
D. J. Rezende, S. A. Eslami, S. Mohamed, P. Battaglia, M. Jaderberg, and N. Heess · 2016
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Multi-view 3d models from single images with a convolutional network
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2016
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Learning category-specific deformable 3d models for object reconstruction
S. Tulsiani, A. Kar, J. Carreira, and J. Malik · 2016
Cited alongside, same era.
Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, B. Freeman, and J. Tenenbaum · 2016
Cited alongside, same era.
Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision
X. Yan, J. Yang, E. Yumer, Y. Guo, and H. Lee · 2016
Cited alongside, same era.
Synthesizing 3d shapes via modeling multi-view depth maps and silhouettes with deep generative networks
A. Arsalan Soltani, H. Huang, J. Wu, T. D. Kulkarni, and J. B. Tenenbaum · 2017
Cited alongside, same era.
A point set generation network for 3d object reconstruction from a single image
H. Fan, H. Su, and L. J. Guibas · 2017
Cited alongside, same era.
Learning efficient point cloud generation for dense 3d object reconstruction
C.-H. Lin, C. Kong, and S. Lucey · 2018
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3D-LMNet: Latent embedding matching for accurate and diverse 3d point cloud reconstruction from a single image
P. Mandikal, K. L. Navaneet, M. Agarwal, and R. V. Babu · 2018
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Deep model-based 6d pose refinement in rgb
F. Manhardt, W. Kehl, N. Navab, and F. Tombari · 2018
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Matryoshka networks: Predicting 3d geometry via nested shape layers
S. R. Richter and S. Roth · 2018
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Pix3d: Dataset and methods for single-image 3d shape modeling
X. Sun, J. Wu, X. Zhang, Z. Zhang, C. Zhang, T. Xue, J. B. Tenenbaum, and W. T. Freeman · 2018
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Multi-view consistency as supervisory signal for learning shape and pose prediction
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C. Häne, S. Tulsiani, and J. Malik · 2017
Cited alongside, same era.
Learning a multi-view stereo machine
A. Kar, C. Häne, and J. Malik · 2017
Cited alongside, same era.
A survey of structure from motion*
O. Özyeşil, V. Voroninski, R. Basri, and A. Singer · 2017
Cited alongside, same era.
Octnet: Learning deep 3d representations at high resolutions
G. Riegler, A. Osman Ulusoy, and A. Geiger · 2017
Cited alongside, same era.
Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
Cited alongside, same era.
Multi-view supervision for single-view reconstruction via differentiable ray consistency
S. Tulsiani, T. Zhou, A. A. Efros, and J. Malik · 2017
Cited alongside, same era.
3densinet: A robust neural network architecture towards 3d volumetric object prediction from 2d image
M. Wang, L. Wang, and Y. Fang · 2017
Cited alongside, same era.
S. Tulsiani, A. A. Efros, and J. Malik · 2018
Later among the works it cites.
Pixel2mesh: Generating 3d mesh models from single rgb images
N. Wang, Y. Zhang, Z. Li, Y. Fu, W. Liu, and Y.-G. Jiang · 2018
Later among the works it cites.
Learning shape priors for single-view 3d completion and reconstruction
J. Wu, C. Zhang, X. Zhang, Z. Zhang, W. T. Freeman, and J. B. Tenenbaum · 2018
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Learning implicit fields for generative shape modeling
Z. Chen and H. Zhang · 2019
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Explaining the ambiguity of object detection and 6d pose from visual data
F. Manhardt, D. M. Arroyo, C. Rupprecht, B. Busam, T. Birdal, N. Navab, and F. Tombari · 2019
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Occupancy networks: Learning 3d reconstruction in function space
L. Mescheder, M. Oechsle, M. Niemeyer, S. Nowozin, and A. Geiger · 2019
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Deepsdf: Learning continuous signed distance functions for shape representation
J. J. Park, P. Florence, J. Straub, R. Newcombe, and S. Lovegrove · 2019
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What do single-view 3d reconstruction networks learn?
M. Tatarchenko, S. R. Richter, R. Ranftl, Z. Li, V. Koltun, and T. Brox · 2019
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Deep single-view 3d object reconstruction with visual hull embedding
H. Wang, J. Yang, W. Liang, and X. Tong · 2019
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Conditional single-view shape generation for multi-view stereo reconstruction
Y. Wei, S. Liu, W. Zhao, and J. Lu · 2019
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Pixel2mesh++: Multi-view 3d mesh generation via deformation
C. Wen, Y. Zhang, Z. Li, and Y. Fu · 2019
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Pix2vox: Context-aware 3d reconstruction from single and multi-view images
H. Xie, H. Yao, X. Sun, S. Zhou, and S. Zhang · 2019
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On the continuity of rotation representations in neural networks
Y. Zhou, C. Barnes, J. Lu, J. Yang, and H. Li · 2019
Later among the works it cites.
Bsp-net: Generating compact meshes via binary space partitioning
Z. Chen, A. Tagliasacchi, and H. Zhang · 2020
Closest in time.
Cvxnet: Learnable convex decomposition
B. Deng, K. Genova, S. Yazdani, S. Bouaziz, G. Hinton, and A. Tagliasacchi · 2020
Closest in time.