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Traditional computer graphics rendering pipeline is designed for procedurally generating 2D quality images from 3D shapes with high performance.
Determining lightness from an image
Berthold K. P. Horn · 1974
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Determining lightness from an image
Berthold K. P. Horn · 1974
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Illumination for computer generated pictures
Bui Tuong Phong · 1975
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Illumination for computer generated pictures
Bui Tuong Phong · 1975
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Efficient algorithms for local and global accessibility shading
Gavin Miller · 1994
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Efficient algorithms for local and global accessibility shading
Gavin Miller · 1994
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Suggestive contours for conveying shape
Doug DeCarlo, Adam Finkelstein, Szymon Rusinkiewicz, and Anthony Santella · 2003
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Simplification and repair of polygonal models using volumetric techniques
F. S. Nooruddin and G. Turk · 2003
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Suggestive contours for conveying shape
Doug DeCarlo, Adam Finkelstein, Szymon Rusinkiewicz, and Anthony Santella · 2003
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Simplification and repair of polygonal models using volumetric techniques
F. S. Nooruddin and G. Turk · 2003
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Real-time video abstraction
Holger Winnemöller, Sven C. Olsen, and Bruce Gooch · 2006
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Real-time video abstraction
Holger Winnemöller, Sven C. Olsen, and Bruce Gooch · 2006
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A 3d face model for pose and illumination invariant face recognition
Pascal Paysan, Reinhard Knothe, Brian Amberg, Sami Romdhani, and Thomas Vetter · 2009
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A 3d face model for pose and illumination invariant face recognition
Pascal Paysan, Reinhard Knothe, Brian Amberg, Sami Romdhani, and Thomas Vetter · 2009
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OpenDR: An approximate differentiable renderer
Matthew M. Loper and Michael J. Black · 2014
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Network in network
Min Lin, Qiang Chen, and Shuicheng Yan · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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3d-assisted image feature synthesis for novel views of an object
Hao Su, Fan Wang, Li Yi, and Leonidas J. Guibas · 2014
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Seeing 3d chairs: exemplar part-based 2d-3d alignment using a large dataset of cad models
Mathieu Aubry, Daniel Maturana, Alexei Efros, Bryan Russell, and Josef Sivic · 2014
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OpenDR: An approximate differentiable renderer
Matthew M. Loper and Michael J. Black · 2014
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Network in network
Min Lin, Qiang Chen, and Shuicheng Yan · 2014
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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3d-assisted image feature synthesis for novel views of an object
Hao Su, Fan Wang, Li Yi, and Leonidas J. Guibas · 2014
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Seeing 3d chairs: exemplar part-based 2d-3d alignment using a large dataset of cad models
Mathieu Aubry, Daniel Maturana, Alexei Efros, Bryan Russell, and Josef Sivic · 2014
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U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P.Fischer, and T. Brox · 2015
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Shape, illumination, and reflectance from shading
Jonathan T Barron and Jitendra Malik · 2015
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Deep convolutional inverse graphics network
Tejas D Kulkarni, William F. Whitney, Pushmeet Kohli, and Josh Tenenbaum · 2015
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Weakly-supervised disentangling with recurrent transformations for 3d view synthesis
Jimei Yang, Scott E Reed, Ming-Hsuan Yang, and Honglak Lee · 2015
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Shapenet: An information-rich 3d model repository
Angel X. Chang, Thomas A. Funkhouser, Leonidas J. Guibas, Pat Hanrahan, Qi-Xing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimm Ba · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Cited alongside, same era.
U-net: Convolutional networks for biomedical image segmentation
O. Ronneberger, P.Fischer, and T. Brox · 2015
Cited alongside, same era.
Shape, illumination, and reflectance from shading
Jonathan T Barron and Jitendra Malik · 2015
Cited alongside, same era.
Deep convolutional inverse graphics network
Transformation-grounded image generation network for novel 3d view synthesis
Eunbyung Park, Jimei Yang, Ersin Yumer, Duygu Ceylan, and Alexander C. Berg · 2017
Later among the works it cites.
Novel views of objects from a single image
K. Rematas, C. H. Nguyen, T. Ritschel, M. Fritz, and T. Tuytelaars · 2017
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Rethinking reprojection: Closing the loop for pose-aware shape reconstruction from a single image
Rui Zhu, Hamed Kiani Galoogahi, Chaoyang Wang, and Simon Lucey · 2017
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MarrNet: 3D Shape Reconstruction via 2.5D Sketches
Jiajun Wu, Yifan Wang, Tianfan Xue, Xingyuan Sun, William T Freeman, and Joshua B Tenenbaum · 2017
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Multi-view supervision for single-view reconstruction via differentiable ray consistency
Shubham Tulsiani, Tinghui Zhou, Alexei A. Efros, and Jitendra Malik · 2017
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Learning detailed face reconstruction from a single image
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Tejas D Kulkarni, William F. Whitney, Pushmeet Kohli, and Josh Tenenbaum · 2015
Cited alongside, same era.
Weakly-supervised disentangling with recurrent transformations for 3d view synthesis
Jimei Yang, Scott E Reed, Ming-Hsuan Yang, and Honglak Lee · 2015
Cited alongside, same era.
Shapenet: An information-rich 3d model repository
Angel X. Chang, Thomas A. Funkhouser, Leonidas J. Guibas, Pat Hanrahan, Qi-Xing Huang, Zimo Li, Silvio Savarese, Manolis Savva, Shuran Song, Hao Su, Jianxiong Xiao, Li Yi, and Fisher Yu · 2015
Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimm Ba · 2015
Cited alongside, same era.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Cited alongside, same era.
Unsupervised learning of 3d structure from images
Danilo Jimenez Rezende, S. M. Ali Eslami, Shakir Mohamed, Peter Battaglia, Max Jaderberg, and Nicolas Heess · 2016
Cited alongside, same era.
Perspective transformer nets: Learning single-view 3d object reconstruction without 3d supervision
Xinchen Yan, Jimei Yang, Ersin Yumer, Yijie Guo, and Honglak Lee · 2016
Cited alongside, same era.
E. Richardson, M. Sela, R. Or-El, and R. Kimmel · 2017
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Weakly supervised 3d reconstruction with adversarial constraint
JunYoung Gwak, Christopher B Choy, Manmohan Chandraker, Animesh Garg, and Silvio Savarese · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens van der Maaten, and Kilian Q Weinberger · 2017
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Learning to generate chairs, tables and cars with convolutional networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Maxim Tatarchenko, and Thomas Brox · 2017
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Photographic image synthesis with cascaded refinement networks
Qifeng Chen and Vladlen Koltun · 2017
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Deep shading: Convolutional neural networks for screen-space shading
Oliver Nalbach, Elena Arabadzhiyska, Dushyant Mehta, Hans-Peter Seidel, and Tobias Ritschel · 2017
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Octree generating networks: Efficient convolutional architectures for high-resolution 3d outputs
Maxim Tatarchenko, Alexey Dosovitskiy, and Thomas Brox · 2017
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O-cnn: Octree-based convolutional neural networks for 3d shape analysis
Peng-Shuai Wang, Yang Liu, Yu-Xiao Guo, Chun-Yu Sun, and Xin Tong · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A. Efros · 2017
Later among the works it cites.
Transformation-grounded image generation network for novel 3d view synthesis
Eunbyung Park, Jimei Yang, Ersin Yumer, Duygu Ceylan, and Alexander C. Berg · 2017
Later among the works it cites.
Novel views of objects from a single image
K. Rematas, C. H. Nguyen, T. Ritschel, M. Fritz, and T. Tuytelaars · 2017
Later among the works it cites.
Neural 3d mesh renderer
Hiroharu Kato, Yoshitaka Ushiku, and Tatsuya Harada · 2018
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Learning to generate and reconstruct 3d meshes with only 2d supervision
Paul Henderson and Vittorio Ferrari · 2018
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Unsupervised training for 3d morphable model regression
Kyle Genova, Forrester Cole, Aaron Maschinot, Aaron Sarna, Daniel Vlasic, and William T. Freeman · 2018
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3d-rcnn: Instance-level 3d object reconstruction via render-and-compare
Abhijit Kundu, Yin Li, and James M. Rehg · 2018
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Neural inverse rendering for general reflectance photometric stereo
Tatsunori Taniai and Takanori Maehara · 2018
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Multi-view consistency as supervisory signal for learning shape and pose prediction
Shubham Tulsiani, Alexei A. Efros, and Jitendra Malik · 2018
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Neural 3d mesh renderer
Hiroharu Kato, Yoshitaka Ushiku, and Tatsuya Harada · 2018
Closest in time.
Learning to generate and reconstruct 3d meshes with only 2d supervision
Paul Henderson and Vittorio Ferrari · 2018
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Unsupervised training for 3d morphable model regression
Kyle Genova, Forrester Cole, Aaron Maschinot, Aaron Sarna, Daniel Vlasic, and William T. Freeman · 2018
Closest in time.
3d-rcnn: Instance-level 3d object reconstruction via render-and-compare
Abhijit Kundu, Yin Li, and James M. Rehg · 2018
Closest in time.
Neural inverse rendering for general reflectance photometric stereo
Tatsunori Taniai and Takanori Maehara · 2018
Closest in time.
Multi-view consistency as supervisory signal for learning shape and pose prediction
Shubham Tulsiani, Alexei A. Efros, and Jitendra Malik · 2018
Closest in time.