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3D-aware image synthesis encompasses a variety of tasks, such as scene generation and novel view synthesis from images.
Animating rotation with quaternion curves
Ken Shoemake · 1985
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli · 2004
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Are we ready for autonomous driving? the kitti vision benchmark suite
Andreas Geiger, Philip Lenz, and Raquel Urtasun · 2012
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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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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Stochastic backpropagation and approximate inference in deep generative models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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ShapeNet: An Information-Rich 3D Model Repository
Angel X. Chang, Thomas Funkhouser, Leonidas Guibas, Pat Hanrahan, Qixing 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 Jimmy Ba · 2015
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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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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Demystifying mmd gans
Mikołaj Bińkowski, Danica J. Sutherland, Michael Arbel, and Arthur Gretton · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei Efros, Eli Shechtman, and Oliver Wang · 2018
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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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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Towards unsupervised learning of generative models for 3d controllable image synthesis
Yiyi Liao, Katja Schwarz, Lars Mescheder, and Andreas Geiger · 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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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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Mvsnerf: Fast generalizable radiance field reconstruction from multi-view stereo
Anpei Chen, Zexiang Xu, Fuqiang Zhao, Xiaoshuai Zhang, Fanbo Xiang, Jingyi Yu, and Hao Su · 2021
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MMGeneration: Openmmlab generative model toolbox and benchmark
MMGeneration Contributors · 2021
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Unconstrained scene generation with locally conditioned radiance fields
Terrance DeVries, Miguel Angel Bautista, Nitish Srivastava, Graham W. Taylor, and Joshua M. Susskind · 2021
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Monocinis: Camera independent monocular 3d object detection using instance segmentation
Jonas Heylen, Mark De Wolf, Bruno Dawagne, Marc Proesmans, Luc Van Gool, Wim Abbeloos, Hazem Abdelkawy, and Daniel Olmeda Reino · 2021
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Codenerf: Disentangled neural radiance fields for object categories
Wonbong Jang and Lourdes Agapito · 2021
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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Denoising diffusion implicit models
Lolnerf: Learn from one look
Daniel Rebain, Mark Matthews, Kwang Moo Yi, Dmitry Lagun, and Andrea Tagliasacchi · 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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Progressive distillation for fast sampling of diffusion models
Tim Salimans and Jonathan Ho · 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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Torch-ngp: a pytorch implementation of instant-ngp
Jiaxiang Tang · 2022
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Jiaming Song, Chenlin Meng, and Stefano Ermon · 2021
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Maximum likelihood training of score-based diffusion models
Yang Song, Conor Durkan, Iain Murray, and Stefano Ermon · 2021
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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 · 2021
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Score-based generative modeling in latent space
Arash Vahdat, Karsten Kreis, and Jan Kautz · 2021
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Diffusion priors in variational autoencoders
Antoine Wehenkel and Gilles Louppe · 2021
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pixelNeRF: Neural radiance fields from one or few images
Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Gaudi: A neural architect for immersive 3d scene generation
Miguel Angel Bautista, Pengsheng Guo, Samira Abnar, Walter Talbott, Alexander Toshev, Zhuoyuan Chen, Laurent Dinh, Shuangfei Zhai, Hanlin Goh, Daniel Ulbricht, Afshin Dehghan, and Josh Susskind · 2022
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Nerfusion: Fusing radiance fields for large-scale scene reconstruction
Xiaoshuai Zhang, Sai Bi, Kalyan Sunkavalli, Hao Su, and Zexiang Xu · 2022
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RenderDiffusion: Image diffusion for 3D reconstruction, inpainting and generation
Titas Anciukevicius, Zexiang Xu, Matthew Fisher, Paul Henderson, Hakan Bilen, Niloy J. Mitra, and Paul Guerrero · 2023
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Factor fields: A unified framework for neural fields and beyond, 2023
Anpei Chen, Zexiang Xu, Xinyue Wei, Siyu Tang, Hao Su, and Andreas Geiger · 2023
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Nerdi: Single-view nerf synthesis with language-guided diffusion as general image priors
Congyue Deng, Chiyu Jiang, Charles R Qi, Xinchen Yan, Yin Zhou, Leonidas Guibas, Dragomir Anguelov, et al · 2023
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Learning controllable 3d diffusion models from single-view images, 2023
Jiatao Gu, Qingzhe Gao, Shuangfei Zhai, Baoquan Chen, Lingjie Liu, and Josh Susskind · 2023
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Nerfdiff: Single-image view synthesis with nerf-guided distillation from 3d-aware diffusion
Jiatao Gu, Alex Trevithick, Kai-En Lin, Josh Susskind, Christian Theobalt, Lingjie Liu, and Ravi Ramamoorthi · 2023
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Vision transformer for nerf-based view synthesis from a single input image
Kai-En Lin, Lin Yen-Chen, Wei-Sheng Lai, Tsung-Yi Lin, Yi-Chang Shih, and Ravi Ramamoorthi · 2023
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Diffrf: Rendering-guided 3d radiance field diffusion
Norman Müller, , Yawar Siddiqui, Lorenzo Porzi, Samuel Rota Bulò, Peter Kontschieder, and Matthias Nießner · 2023
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Dreamfusion: Text-to-3d using 2d diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, and Ben Mildenhall · 2023
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Generative modelling with inverse heat dissipation
Severi Rissanen, Markus Heinonen, and Arno Solin · 2023
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3d neural field generation using triplane diffusion
J Ryan Shue, Eric Ryan Chan, Ryan Po, Zachary Ankner, Jiajun Wu, and Gordon Wetzstein · 2023
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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, and Baining Guo · 2023
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Novel view synthesis with diffusion models
Daniel Watson, William Chan, Ricardo Martin-Brualla, Jonathan Ho, Andrea Tagliasacchi, and Mohammad Norouzi · 2023
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Sparsefusion: Distilling view-conditioned diffusion for 3d reconstruction
Zhizhuo Zhou and Shubham Tulsiani · 2023
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