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While recent generative models for 2D images achieve impressive visual results, they clearly lack the ability to perform 3D reasoning.
Laplacian surface editing
O. Sorkine, D. Cohen-Or, Y. Lipman, M. Alexa, C. Rössl, and H.-P. Seidel · 2004
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
The Caltech-UCSD Birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
Earlier work this paper cites.
Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
Earlier work this paper cites.
Auto-encoding variational Bayes
D. P. Kingma and M. Welling · 2014
Earlier work this paper cites.
Opendr: An approximate differentiable renderer
M. M. Loper and M. J. Black · 2014
Earlier work this paper cites.
Beyond PASCAL: A benchmark for 3D object detection in the wild
Y. Xiang, R. Mottaghi, and S. Savarese · 2014
Earlier work this paper cites.
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
Earlier work this paper cites.
Learning a predictable and generative vector representation for objects
R. Girdhar, D. F. Fouhey, M. Rodriguez, and A. Gupta · 2016
Earlier work this paper cites.
Deconvolution and checkerboard artifacts
A. Odena, V. Dumoulin, and C. Olah · 2016
Earlier work this paper cites.
Unsupervised learning of 3d structure from images
D. J. Rezende, S. A. Eslami, S. Mohamed, P. Battaglia, M. Jaderberg, and N. Heess · 2016
Earlier work this paper cites.
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
Earlier work this paper cites.
Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision
X. Yan, J. Yang, E. Yumer, Y. Guo, and H. Lee · 2016
Earlier work this paper cites.
A point set generation network for 3d object reconstruction from a single image
H. Fan, H. Su, and L. J. Guibas · 2017
Earlier work this paper cites.
Weakly supervised 3d reconstruction with adversarial constraint
J. Gwak, C. B. Choy, M. Chandraker, A. Garg, and S. Savarese · 2017
Earlier work this paper cites.
Hierarchical surface prediction for 3d object reconstruction
C. Häne, S. Tulsiani, and J. Malik · 2017
Earlier work this paper cites.
Mask R-CNN
K. He, G. Gkioxari, P. Dollár, and R. Girshick · 2017
Earlier work this paper cites.
GANs trained by a two time-scale update rule converge to a local Nash equilibrium
M. Heusel, H. Ramsauer, T. Unterthiner, B. Nessler, and S. Hochreiter · 2017
Earlier work this paper cites.
Image-to-image translation with conditional adversarial networks
P. Isola, J.-Y. Zhu, T. Zhou, and A. A. Efros · 2017
Earlier work this paper cites.
Improved adversarial systems for 3d object generation and reconstruction
E. J. Smith and D. Meger · 2017
Earlier work this paper cites.
Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
M. Tatarchenko, A. Dosovitskiy, and T. Brox · 2017
Earlier work this paper cites.
Multi-view supervision for single-view reconstruction via differentiable ray consistency
S. Tulsiani, T. Zhou, A. A. Efros, and J. Malik · 2017
Earlier work this paper cites.
Attention is all you need
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, Ł. Kaiser, and I. Polosukhin · 2017
Earlier work this paper cites.
Silnet : Single- and multi-view reconstruction by learning from silhouettes
O. Wiles and A. Zisserman · 2017
Cited alongside, same era.
Marrnet: 3d shape reconstruction via 2.5d sketches
J. Wu, Y. Wang, T. Xue, X. Sun, B. Freeman, and J. Tenenbaum · 2017
Cited alongside, same era.
3d object reconstruction from a single depth view with adversarial learning
B. Yang, H. Wen, S. Wang, R. Clark, A. Markham, and N. Trigoni · 2017
Cited alongside, same era.
LR-GAN: layered recursive generative adversarial networks for image generation
J. Yang, A. Kannan, D. Batra, and D. Parikh · 2017
Cited alongside, same era.
StackGAN: Text to photo-realistic image synthesis with stacked generative adversarial networks
H. Zhang, T. Xu, H. Li, S. Zhang, X. Wang, X. Huang, and D. N. Metaxas · 2017
Cited alongside, same era.
Unpaired image-to-image translation using cycle-consistent adversarial networks
The unreasonable effectiveness of deep features as a perceptual metric
R. Zhang, P. Isola, A. A. Efros, E. Shechtman, and O. Wang · 2018
Later among the works it cites.
Visual object networks: Image generation with disentangled 3d representations
J.-Y. Zhu, Z. Zhang, C. Zhang, J. Wu, A. Torralba, J. Tenenbaum, and B. Freeman · 2018
Later among the works it cites.
Large scale GAN training for high fidelity natural image synthesis
A. Brock, J. Donahue, and K. Simonyan · 2019
Later among the works it cites.
Learning to predict 3d objects with an interpolation-based differentiable renderer
W. Chen, H. Ling, J. Gao, E. Smith, J. Lehtinen, A. Jacobson, and S. Fidler · 2019
Later among the works it cites.
Deep fakes: A looming challenge for privacy, democracy, and national security
B. Chesney and D. Citron · 2019
Later among the works it cites.
Escaping plato’s cave: 3d shape from adversarial rendering
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J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros · 2017
Cited alongside, same era.
Rethinking reprojection: Closing the loop for pose-aware shape reconstruction from a single image
R. Zhu, H. Kiani Galoogahi, C. Wang, and S. Lucey · 2017
Cited alongside, same era.
Learning representations and generative models for 3d point clouds
P. Achlioptas, O. Diamanti, I. Mitliagkas, and L. Guibas · 2018
Cited alongside, same era.
Structure-aware shape synthesis
E. Balashova, V. Singh, J. Wang, B. Teixeira, T. Chen, and T. Funkhouser · 2018
Cited alongside, same era.
Multiresolution tree networks for 3d point cloud processing
M. Gadelha, R. Wang, and S. Maji · 2018
Cited alongside, same era.
Inferring semantic layout for hierarchical text-to-image synthesis
S. Hong, D. Yang, J. Choi, and H. Lee · 2018
Cited alongside, same era.
Unsupervised learning of shape and pose with differentiable point clouds
E. Insafutdinov and A. Dosovitskiy · 2018
Cited alongside, same era.
P. Henzler, N. J. Mitra, and T. Ritschel · 2019
Later among the works it cites.
A style-based generator architecture for generative adversarial networks
T. Karras, S. Laine, and T. Aila · 2019
Later among the works it cites.
Controllable text-to-image generation
B. Li, X. Qi, T. Lukasiewicz, and P. H. S. Torr · 2019
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Soft rasterizer: A differentiable renderer for image-based 3d reasoning
S. Liu, T. Li, W. Chen, and H. Li · 2019
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Challenging common assumptions in the unsupervised learning of disentangled representations
F. Locatello, S. Bauer, M. Lucic, S. Gelly, B. Schölkopf, and O. Bachem · 2019
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Instance-aware image-to-image translation
S. Mo, M. Cho, and J. Shin · 2019
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Hologan: Unsupervised learning of 3d representations from natural images
T. Nguyen-Phuoc, C. Li, L. Theis, C. Richardt, and Y.-L. Yang · 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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Semantic image synthesis with spatially-adaptive normalization
T. Park, M.-Y. Liu, T.-C. Wang, and J.-Y. Zhu · 2019
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FineGAN: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery
K. K. Singh, U. Ojha, and Y. J. Lee · 2019
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Image synthesis from reconfigurable layout and style
W. Sun and T. Wu · 2019
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The unusual effectiveness of averaging in GAN training
Y. Yazıcı, C.-S. Foo, S. Winkler, K.-H. Yap, G. Piliouras, and V. Chandrasekhar · 2019
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Self-attention generative adversarial networks
H. Zhang, I. Goodfellow, D. Metaxas, and A. Odena · 2019
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Image generation from layout
B. Zhao, L. Meng, W. Yin, and L. Sigal · 2019
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https://theblog.adobe.com/state-of-ai-in-animation/
State of AI in animation · 2020
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http://pth.izitru.com/
Photo tampering throughout history · 2020
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Leveraging 2d data to learn textured 3d mesh generation
P. Henderson, V. Tsiminaki, and C. H. Lampert · 2020
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Self-supervised viewpoint learning from image collections
S. K. Mustikovela, V. Jampani, S. D. Mello, S. Liu, U. Iqbal, C. Rother, and J. Kautz · 2020
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Controlling style and semantics in weakly-supervised image generation
D. Pavllo, A. Lucchi, and T. Hofmann · 2020
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