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We propose StyleNeRF, a 3D-aware generative model for photo-realistic high-resolution image synthesis with high multi-view consistency, which can be trained on unstructured 2D images.
Training generative adversarial networks with limited data
Tero Karras, Miika Aittala, Janne Hellsten, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2006
Earlier work this paper cites.
Generative adversarial nets
Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron C. Courville, and Yoshua Bengio · 2014
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A large-scale car dataset for fine-grained categorization and verification
Linjie Yang, Ping Luo, Chen Change Loy, and Xiaoou Tang · 2015
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Structure-from-motion revisited
Johannes Lutz Schönberger and Jan-Michael Frahm · 2016
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Real-time single image and video super-resolution using an efficient sub-pixel convolutional neural network
Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P Aitken, Rob Bishop, Daniel Rueckert, and Zehan Wang · 2016
Earlier work this paper cites.
Generative multi-adversarial networks, 2017
Ishan Durugkar, Ian Gemp, and Sridhar Mahadevan · 2017
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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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Arbitrary style transfer in real-time with adaptive instance normalization
Xun Huang and Serge Belongie · 2017
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Progressive growing of gans for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2017
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Mikołaj Bińkowski, Danica J Sutherland, Michael Arbel, and Arthur Gretton · 2018
Earlier work this paper cites.
Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2018
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Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
Earlier work this paper cites.
Dropout-gan: Learning from a dynamic ensemble of discriminators
Gonçalo Mordido, Haojin Yang, and C. Meinel · 2018
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Online adaptative curriculum learning for gans
Thang Doan, J. Monteiro, Isabela Albuquerque, Bogdan Mazoure, A. Durand, Joelle Pineau, and R. Devon Hjelm · 2019
Earlier work this paper cites.
The deepfake detection challenge (dfdc) preview dataset
Brian Dolhansky, Russ Howes, Ben Pflaum, Nicole Baram, and Cristian Canton Ferrer · 2019
Cited alongside, same era.
Escaping plato’s cave: 3d shape from adversarial rendering
Philipp Henzler, Niloy J. Mitra, and Tobias Ritschel · 2019
Cited alongside, same era.
A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
Cited alongside, same era.
Occupancy networks: Learning 3d reconstruction in function space
Lars Mescheder, Michael Oechsle, Michael Niemeyer, Sebastian Nowozin, and Andreas Geiger · 2019
Cited alongside, same era.
Implicit surface representations as layers in neural networks
Mateusz Michalkiewicz, Jhony K. Pontes, Dominic Jack, Mahsa Baktashmotlagh, and Anders Eriksson · 2019
Cited alongside, same era.
Ganspace: Discovering interpretable gan controls
Erik Härkönen, Aaron Hertzmann, Jaakko Lehtinen, and Sylvain Paris · 2020
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Neural sparse voxel fields
Lingjie Liu, Jiatao Gu, Kyaw Zaw Lin, Tat-Seng Chua, and Christian Theobalt · 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
Later among the works it cites.
Blockgan: Learning 3d object-aware scene representations from unlabelled images
Thu Nguyen-Phuoc, Christian Richardt, Long Mai, Yong-Liang Yang, and Niloy Mitra · 2020
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Convolutional occupancy networks
Songyou Peng, Michael Niemeyer, Lars M. Mescheder, Marc Pollefeys, and Andreas Geiger · 2020
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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
Cited alongside, same era.
Differentiable volumetric rendering: Learning implicit 3d representations without 3d supervision
Michael Niemeyer, Lars Mescheder, Michael Oechsle, and Andreas Geiger · 2019
Cited alongside, same era.
Deepsdf: Learning continuous signed distance functions for shape representation
Jeong Joon Park, Peter Florence, Julian Straub, Richard Newcombe, and Steven Lovegrove · 2019
Cited alongside, same era.
Scene representation networks: Continuous 3d-structure-aware neural scene representations
Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
Cited alongside, same era.
Self-attention generative adversarial networks
Han Zhang, Ian Goodfellow, Dimitris Metaxas, and Augustus Odena · 2019
Cited alongside, same era.
Making convolutional networks shift-invariant again
Richard Zhang · 2019
Cited alongside, same era.
Image2stylegan++: How to edit the embedded images?
Rameen Abdal, Yipeng Qin, and Peter Wonka · 2020
Cited alongside, same era.
Later among the works it cites.
Graf: Generative radiance fields for 3d-aware image synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
Later among the works it cites.
Interpreting the latent space of gans for semantic face editing
Yujun Shen, Jinjin Gu, Xiaoou Tang, and Bolei Zhou · 2020
Later among the works it cites.
Nerf++: Analyzing and improving neural radiance fields
Kai Zhang, Gernot Riegler, Noah Snavely, and Vladlen Koltun · 2020
Later among the works it cites.
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
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Alias-free generative adversarial networks
Tero Karras, Miika Aittala, Samuli Laine, Erik Härkönen, Janne Hellsten, Jaakko Lehtinen, and Timo Aila · 2021
Closest in time.
Freestylegan: Free-view editable portrait rendering with the camera manifold
Thomas Leimkühler and George Drettakis · 2021
Closest in time.
Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Gan-control: Explicitly controllable gans, 2021
Alon Shoshan, Nadav Bhonker, Igor Kviatkovsky, and Gerard Medioni · 2021
Closest in time.