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Recent 3D generative models have achieved remarkable performance in synthesizing high resolution photorealistic images with view consistency and detailed 3D shapes, but training them for diverse domains is challenging since it requires massive training images and their camera distribution information.
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Shapenet: An information-rich 3d model repository
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U-net: Convolutional networks for biomedical image segmentation
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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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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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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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Image generation from small datasets via batch statistics adaptation
Atsuhiro Noguchi and Tatsuya Harada · 2019
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Scene representation networks: Continuous 3d-structure-aware neural scene representations
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Unsupervised generative 3d shape learning from natural images
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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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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Adversarial score matching and improved sampling for image generation
Alexia Jolicoeur-Martineau, Rémi Piché-Taillefer, Rémi Tachet des Combes, and Ioannis Mitliagkas · 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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Towards unsupervised learning of generative models for 3d controllable image synthesis
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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
B Mildenhall, PP Srinivasan, M Tancik, JT Barron, R Ramamoorthi, and R Ng · 2020
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Freeze the discriminator: a simple baseline for fine-tuning gans
Sangwoo Mo, Minsu Cho, and Jinwoo Shin · 2020
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Blockgan: Learning 3d object-aware scene representations from unlabelled images
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Justin NM Pinkney and Doron Adler · 2020
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Few-shot adaptation of generative adversarial networks
Esther Robb, Wen-Sheng Chu, Abhishek Kumar, and Jia-Bin Huang · 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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Denoising diffusion implicit models
Jiaming Song, Chenlin Meng, and Stefano Ermon · 2020
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Score-based generative modeling through stochastic differential equations
Yang Song, Jascha Sohl-Dickstein, Diederik P Kingma, Abhishek Kumar, Stefano Ermon, and Ben Poole · 2020
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Minegan: effective knowledge transfer from gans to target domains with few images
Yaxing Wang, Abel Gonzalez-Garcia, David Berga, Luis Herranz, Fahad Shahbaz Khan, and Joost van de Weijer · 2020
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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Derf: Decomposed radiance fields
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Christian Reiser, Songyou Peng, Yiyi Liao, and Andreas Geiger · 2021
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Lifting 2d stylegan for 3d-aware face generation
Yichun Shi, Divyansh Aggarwal, and Anil K Jain · 2021
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Nerv: Neural reflectance and visibility fields for relighting and view synthesis
Pratul P Srinivasan, Boyang Deng, Xiuming Zhang, Matthew Tancik, Ben Mildenhall, and Jonathan T Barron · 2021
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Nerf++: Analyzing and improving neural radiance fields
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
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Mark Boss, Raphael Braun, Varun Jampani, Jonathan T Barron, Ce Liu, and Hendrik Lensch · 2021
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pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
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Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
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Diffusion models beat gans on image synthesis
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Regularizing generative adversarial networks under limited data
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Volume rendering of neural implicit surfaces
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Plenoctrees for real-time rendering of neural radiance fields
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pixelnerf: Neural radiance fields from one or few images
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Hyperdomainnet: Universal domain adaptation for generative adversarial networks
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