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3D-aware generative models have shown that the introduction of 3D information can lead to more controllable image generation.
Cat head detection - how to effectively exploit shape and texture features
Weiwei Zhang, Jian Sun, and Xiaoou Tang · 2008
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Transforming auto-encoders
Geoffrey E. Hinton, Alex Krizhevsky, and Sida D. Wang · 2011
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Representation learning: A review and new perspectives
Y. Bengio, A. Courville, and P. Vincent · 2013
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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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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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Lsun: Construction of a large-scale image dataset using deep learning with humans in the loop
Fisher Yu, Yinda Zhang, Shuran Song, Ari Seff, and Jianxiong Xiao · 2015
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Infogan: Interpretable representation learning by information maximizing generative adversarial nets
Xi Chen, Yan Duan, Rein Houthooft, John Schulman, Ilya Sutskever, and Pieter Abbeel · 2016
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Unsupervised representation learning with deep convolutional generative adversarial networks
Alec Radford, Luke Metz, and Soumith Chintala · 2016
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Rethinking atrous convolution for semantic image segmentation
Liang-Chieh Chen, George Papandreou, Florian Schroff, and Hartwig Adam · 2017
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Unsupervised learning of disentangled representations from video
Emily L Denton and vighnesh Birodkar · 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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beta-vae: Learning basic visual concepts with a constrained variational framework
Irina Higgins, Loic Matthey, Arka Pal, Christopher Burgess, Xavier Glorot, Matthew Botvinick, Shakir Mohamed, and Alexander Lerchner · 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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Lr-gan: Layered recursive generative adversarial networks for image generation
Jianwei Yang, Anitha Kannan, Dhruv Batra, and Devi Parikh · 2017
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Disentangling factors of variation by mixing them
Qiyang Hu, Attila Szabó, Tiziano Portenier, Paolo Favaro, and Matthias Zwicker · 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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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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Emergence of object segmentation in perturbed generative models
Adam Bielski and Paolo Favaro · 2019
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Large scale GAN training for high fidelity natural image synthesis
Andrew Brock, Jeff Donahue, and Karen Simonyan · 2019
Cited alongside, same era.
Learning implicit fields for generative shape modeling
Zhiqin Chen and Hao Zhang · 2019
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Learning shape templates with structured implicit functions
Kyle Genova, Forrester Cole, Daniel Vlasic, Aaron Sarna, William T Freeman, and Thomas Funkhouser · 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
The hessian penalty: A weak prior for unsupervised disentanglement
William S. Peebles, John Peebles, Jun-Yan Zhu, Alexei A. Efros, and Antonio Torralba · 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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Graf: Generative radiance fields for 3d-aware image synthesis
Katja Schwarz, Yiyi Liao, Michael Niemeyer, and Andreas Geiger · 2020
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Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien N.P. Martel, Alexander W. Bergman, David B. Lindell, and Gordon Wetzstein · 2020
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Fourier features let networks learn high frequency functions in low dimensional domains
Matthew Tancik, Pratul P. Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T. Barron, and Ren Ng · 2020
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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.
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.
Pifu: Pixel-aligned implicit function for high-resolution clothed human digitization
Shunsuke Saito, Zeng Huang, Ryota Natsume, Shigeo Morishima, Angjoo Kanazawa, and Hao Li · 2019
Cited alongside, same era.
Finegan: Unsupervised hierarchical disentanglement for fine-grained object generation and discovery
Krishna Kumar Singh, Utkarsh Ojha, and Yong Jae Lee · 2019
Cited alongside, same era.
Neural unsigned distance fields for implicit function learning
Julian Chibane, Aymen Mir, and Gerard Pons-Moll · 2020
Cited alongside, same era.
Stargan v2: Diverse image synthesis for multiple domains
Yunjey Choi, Youngjung Uh, Jaejun Yoo, and Jung-Woo Ha · 2020
Cited alongside, same era.
Cnn-generated images are surprisingly easy to spot… for now
Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, and Alexei A. Efros · 2020
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Styleflow: Attribute-conditioned exploration of stylegan-generated images using conditional continuous normalizing flows
Rameen Abdal, Peihao Zhu, Niloy Mitra, and Peter Wonka · 2021
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pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
Eric Chan, Marco Monteiro, Petr Kellnhofer, Jiajun Wu, and Gordon Wetzstein · 2021
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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
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Learning continuous image representation with local implicit image function
Yinbo Chen, Sifei Liu, and Xiaolong Wang · 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
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Tryongan: Body-aware try-on via layered interpolation
Kathleen M Lewis, Srivatsan Varadharajan, and Ira Kemelmacher-Shlizerman · 2021
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Collaging class-specific gans for semantic image synthesis
Yuheng Li, Yijun Li, Jingwan Lu, Eli Shechtman, Yong Jae Lee, and Krishna Kumar Singh · 2021
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Partgan: Weakly-supervised part decomposition for image generation and segmentation
Yuheng Li, Krishna Kumar Singh, Yang Xue, and Yong Jae Lee · 2021
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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Styleclip: Text-driven manipulation of stylegan imagery
Or Patashnik, Zongze Wu, Eli Shechtman, Daniel Cohen-Or, and Dani Lischinski · 2021
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Stylespace analysis: Disentangled controls for stylegan image generation
Zongze Wu, Dani Lischinski, and Eli Shechtman · 2021
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