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Generating images with both photorealism and multiview 3D consistency is crucial for 3D-aware GANs, yet existing methods struggle to achieve them simultaneously.
Ray tracing volume densities
James T Kajiya and Brian P Von Herzen · 1984
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Epipolar-plane image analysis: An approach to determining structure from motion
Robert C Bolles, H Harlyn Baker, and David H Marimont · 1987
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Marching cubes: A high resolution 3D surface construction algorithm
William E Lorensen and Harvey E Cline · 1987
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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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GANs trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Which training methods for GANs do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
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Escaping plato’s cave: 3D shape from adversarial rendering
Philipp Henzler, Niloy J Mitra, and Tobias Ritschel · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Occupancy networks: Learning 3D reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
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Hologan: Unsupervised learning of 3D representations from natural images
Thu Nguyen-Phuoc, Chuan Li, Lucas Theis, Christian Richardt, and Yong-Liang Yang · 2019
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DeepSDF: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
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Scene representation networks: continuous 3D-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
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Unsupervised generative 3D shape learning from natural images
Attila Szabó, Givi Meishvili, and Paolo Favaro · 2019
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StarGAN v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
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GANSpace: Discovering interpretable GAN controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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On the “steerability” of generative adversarial networks
Ali Jahanian, Lucy Chai, and Phillip Isola · 2020
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Training generative adversarial networks with limited data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2020
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Analyzing and improving the image quality of styleGAN
Tero Karras, Samuli Laine, Miika Aittala, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2020
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Nerf: Representing scenes as neural radiance fields for view synthesis
Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2020
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GRAF: Generative radiance fields for 3D-aware image synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
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Interpreting the latent space of GANs for semantic face editing
Yujun Shen, Jinjin Gu, Xiaoou Tang, and Bolei Zhou · 2020
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Implicit neural representations with periodic activation functions
Cips-3d: A 3D-aware generator of gans based on conditionally-independent pixel synthesis
Peng Zhou, Lingxi Xie, Bingbing Ni, and Qi Tian · 2021
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Efficient geometry-aware 3D generative adversarial networks
Eric R Chan, Connor Z Lin, Matthew A Chan, Koki Nagano, Boxiao Pan, Shalini De Mello, Orazio Gallo, Leonidas Guibas, Jonathan Tremblay, Sameh Khamis, et al · 2022
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GRAM: Generative radiance manifolds for 3D-aware image generation
Yu Deng, Jiaolong Yang, Jianfeng Xiang, and Xin Tong · 2022
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StyleNeRF: A style-based 3D aware generator for high-resolution image synthesis
Jiatao Gu, Lingjie Liu, Peng Wang, and Christian Theobalt · 2022
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Magic3D: High-resolution text-to-3D content creation
Chen-Hsuan Lin, Jun Gao, Luming Tang, Towaki Takikawa, Xiaohui Zeng, Xun Huang, Karsten Kreis, Sanja Fidler, Ming-Yu Liu, and Tsung-Yi Lin · 2022
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Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
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pi-GAN: Periodic implicit generative adversarial networks for 3D-aware image synthesis
Eric R Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2021
Cited alongside, same era.
Unconstrained scene generation with locally conditioned radiance fields
Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W Taylor, and Joshua M Susskind · 2021
Cited alongside, same era.
Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
Cited alongside, same era.
Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
Cited alongside, same era.
Unisurf: Unifying neural implicit surfaces and radiance fields for multi-view reconstruction
Michael Oechsle, Songyou Peng, and Andreas Geiger · 2021
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Do 2D GANs know 3D shape? unsupervised 3D shape reconstruction from 2d image gans
Xingang Pan, Bo Dai, Ziwei Liu, Chen Change Loy, and Ping Luo · 2021
Cited alongside, same era.
Later among the works it cites.
StyleSDF: High-resolution 3D-consistent image and geometry generation
Roy Or-El, Xuan Luo, Mengyi Shan, Eli Shechtman, Jeong Joon Park, and Ira Kemelmacher-Shlizerman · 2022
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Gan2x: Non-lambertian inverse rendering of image gans
Xingang Pan, Ayush Tewari, Lingjie Liu, and Christian Theobalt · 2022
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Dreamfusion: Text-to-3D using 2D diffusion
Ben Poole, Ajay Jain, Jonathan T Barron, and Ben Mildenhall · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Raphael Gontijo-Lopes, Burcu Karagol Ayan, Tim Salimans, et al · 2022
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VoxGRAF: Fast 3D-aware image synthesis with sparse voxel grids
Katja Schwarz, Axel Sauer, Michael Niemeyer, Yiyi Liao, and Andreas Geiger · 2022
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EpiGRAF: Rethinking training of 3D GANs
Ivan Skorokhodov, Sergey Tulyakov, Yiqun Wang, and Peter Wonka · 2022
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3D-aware image synthesis via learning structural and textural representations
Yinghao Xu, Sida Peng, Ceyuan Yang, Yujun Shen, and Bolei Zhou · 2022
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Giraffe HD: A high-resolution 3D-aware generative model
Yang Xue, Yuheng Li, Krishna Kumar Singh, and Yong Jae Lee · 2022
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Multi-view consistent generative adversarial networks for 3D-aware image synthesis
Xuanmeng Zhang, Zhedong Zheng, Daiheng Gao, Bang Zhang, Pan Pan, and Yi Yang · 2022
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Generative multiplane images: Making a 2D GAN 3D-aware
Xiaoming Zhao, Fangchang Ma, David Güera, Zhile Ren, Alexander G Schwing, and Alex Colburn · 2022
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Rodin: A generative model for sculpting 3D digital avatars using diffusion
Tengfei Wang, Bo Zhang, Ting Zhang, Shuyang Gu, Jianmin Bao, Tadas Baltrusaitis, Jingjing Shen, Dong Chen, Fang Wen, Qifeng Chen, et al · 2023
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GRAM-HD: 3D-consistent image generation at high resolution with generative radiance manifolds
Jianfeng Xiang, Jiaolong Yang, Yu Deng, and Xin Tong · 2023
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