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Neural Radiance Field (NeRF) has emerged as a compelling method to represent 3D objects and scenes for photo-realistic rendering.
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Zhiqin Chen and Hao Zhang · 2019
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Neural volumes: Learning dynamic renderable volumes from images
Stephen Lombardi, Tomas Simon, Jason Saragih, Gabriel Schwartz, Andreas Lehrmann, and Yaser Sheikh · 2019
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Local light field fusion: Practical view synthesis with prescriptive sampling guidelines
Ben Mildenhall, Pratul P Srinivasan, Rodrigo Ortiz-Cayon, Nima Khademi Kalantari, Ravi Ramamoorthi, Ren Ng, and Abhishek Kar · 2019
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Vincent Sitzmann, Michael Zollhöfer, and Gordon Wetzstein · 2019
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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
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Giraffe: Representing scenes as compositional generative neural feature fields
Michael Niemeyer and Andreas Geiger · 2021
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Nerfies: Deformable neural radiance fields
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Kilonerf: Speeding up neural radiance fields with thousands of tiny mlps
Christian Reiser, Songyou Peng, Yiyi Liao, and Andreas Geiger · 2021
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Direct voxel grid optimization: Super-fast convergence for radiance fields reconstruction
Cheng Sun, Min Sun, and Hwann-Tzong Chen · 2021
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Clip-nerf: Text-and-image driven manipulation of neural radiance fields
Can Wang, Menglei Chai, Mingming He, Dongdong Chen, and Jing Liao · 2021
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Graf: Generative radiance fields for 3d-aware image synthesis
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Nerf++: Analyzing and improving neural radiance fields
Kai Zhang, Gernot Riegler, Noah Snavely, and Vladlen Koltun · 2020
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields, 2021
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Mip-nerf 360: Unbounded anti-aliased neural radiance fields
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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 · 2021
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pi-gan: Periodic implicit generative adversarial networks for 3d-aware image synthesis
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Neus: Learning neural implicit surfaces by volume rendering for multi-view reconstruction
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Neutex: Neural texture mapping for volumetric neural rendering
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Learning object-compositional neural radiance field for editable scene rendering
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Volume rendering of neural implicit surfaces
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Towards efficient tensor decomposition-based dnn model compression with optimization framework
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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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Nerfactor: Neural factorization of shape and reflectance under an unknown illumination
Xiuming Zhang, Pratul P Srinivasan, Boyang Deng, Paul Debevec, William T Freeman, and Jonathan T Barron · 2021
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Tensorf: Tensorial radiance fields
Anpei Chen, Zexiang Xu, Andreas Geiger, Jingyi Yu, and Hao Su · 2022
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Control-nerf: Editable feature volumes for scene rendering and manipulation
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Instant neural graphics primitives with a multiresolution hash encoding
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Plenoxels: Radiance fields without neural networks
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