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We present a transformation-grounded image generation network for novel 3D view synthesis from a single image.
A review of image-based rendering techniques
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Automatic photo pop-up
D. Hoiem, A. A. Efros, and M. Hebert · 2005
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Space-time completion of video
Y. Wexler, E. Shechtman, and M. Irani · 2007
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Patchmatch: A randomized correspondence algorithm for structural image editing
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Transforming auto-encoders
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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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3d object manipulation in a single photograph using stock 3d models
N. Kholgade, T. Simon, A. Efros, and Y. Sheikh · 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, J. Xiao, L. Yi, and F. Yu · 2015
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Flownet: Learning optical flow with convolutional networks
A. Dosovitskiy, P. Fischery, E. Ilg, C. Hazirbas, V. Golkov, P. van der Smagt, D. Cremers, T. Brox, et al · 2015
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Learning to generate chairs with convolutional neural networks
A. Dosovitskiy, J. T. Springenberg, and T. Brox · 2015
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Multi-view stereo: A tutorial
Y. Furukawa · 2015
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Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and K. Kavukcuoglu · 2015
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Deep convolutional inverse graphics network
T. D. Kulkarni, W. F. Whitney, P. Kohli, and J. B. Tenenbaum · 2015
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Learning deconvolution network for semantic segmentation
H. Noh, S. Hong, and B. Han · 2015
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Render for cnn: Viewpoint estimation in images using cnns trained with rendered 3d model views
H. Su, C. R. Qi, Y. Li, and L. J. Guibas · 2015
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Weakly-supervised disentangling with recurrent transformations for 3d view synthesis
J. Yang, S. Reed, M.-H. Yang, and H. Lee · 2015
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https://github.com/cdcseacave/openMVS
openmvs: open multi-view stereo reconstruction library · 2016
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Dynamic filter networks
B. D. Brabandere, X. Jia, T. Tuytelaars, and L. V. Gool · 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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Unsupervised learning for physical interaction through video prediction
C. Finn, I. Goodfellow, and S. Levine · 2016
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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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Unsupervised representation learning with deep convolutional generative adversarial networks
A. Radford, L. Metz, and S. Chintala · 2016
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Novel views of objects from a single image
K. Rematas, C. Nguyen, T. Ritschel, M. Fritz, and T. Tuytelaars · 2016
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Improved techniques for training gans
T. Salimans, I. Goodfellow, W. Zaremba, V. Cheung, A. Radford, and X. chen · 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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Texture networks: Feed-forward synthesis of textures and stylized images
D. Ulyanov, V. Lebedev, A. Vedaldi, and V. Lempitsky · 2016
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Texture synthesis using shallow convolutional networks with random filters
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Unsupervised cnn for single view depth estimation: Geometry to the rescue
R. Garg, V. K. BG, G. Carneiro, and I. Reid · 2016
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A powerful generative model using random weights for the deep image representation
K. He, Y. Wang, and J. Hopcroft · 2016
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Perceptual losses for real-time style transfer and super-resolution
J. Johnson, A. Alahi, and L. Fei-Fei · 2016
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Generating images part by part with composite generative adversarial networks
H. Kwak and B.-T. Zhang · 2016
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Discriminative regularization for generative models
A. Lamb, V. Dumoulin, and A. Courville · 2016
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Autoencoding beyond pixels using a learned similarity metric
A. B. L. Larsen, S. K. Sønderby, H. Larochelle, and OleWinther · 2016
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I. Ustyuzhaninov, W. Brendel, L. Gatys, and M. Bethge · 2016
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Pixel recurrent neural networks
A. van den Oord, N. Kalchbrenner, and K. Kavukcuoglu · 2016
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Shape completion enabled robotic grasping
J. Varley, C. DeChant, A. Richardson, A. Nair, J. Ruales, and P. Allen · 2016
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Generating videos with scene dynamics
C. Vondrick, H. Pirsiavash, and A. Torralba · 2016
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An uncertain future: Forecasting from static images using variational autoencoders
J. Walker, C. Doersch, A. Gupta, and M. Hebert · 2016
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Learning a probabilistic latent space of object shapes via 3d generative-adversarial modeling
J. Wu, C. Zhang, T. Xue, W. T. Freeman, and J. B. Tenenbaum · 2016
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Visual dynamics: Probabilistic future frame synthesis via cross convolutional networks
T. Xue, J. Wu, K. L. Bouman, and W. T. Freeman · 2016
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Attribute2image: Conditional image generation from visual attributes
X. Yan, J. Y. K. Sohn, and H. Lee · 2016
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Learning semantic deformation flows with 3d convolutional networks
M. E. Yumer and N. J. Mitra · 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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Deep view morphing
D. Ji, J. Kwon, M. McFarland, and S. Savarese · 2017
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