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Neural Radiance Fields (NeRF) has demonstrated remarkable 3D reconstruction capabilities with dense view images.
Ray tracing volume densities
James T Kajiya and Brian P Von Herzen · 1984
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Optical models for direct volume rendering
Nelson Max · 1995
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Depth map prediction from a single image using a multi-scale deep network
David Eigen, Christian Puhrsch, and Rob Fergus · 2014
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Large scale multi-view stereopsis evaluation
Rasmus Jensen, Anders Dahl, George Vogiatzis, Engin Tola, and Henrik Aanæs · 2014
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Digging into self-supervised monocular depth estimation
Clément Godard, Oisin Mac Aodha, Michael Firman, and Gabriel J Brostow · 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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Image quality assessment through fsim, ssim, mse and psnr—a comparative study
Umme Sara, Morium Akter, and Mohammad Shorif Uddin · 2019
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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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Towards robust monocular depth estimation: Mixing datasets for zero-shot cross-dataset transfer
René Ranftl, Katrin Lasinger, David Hafner, Konrad Schindler, and Vladlen Koltun · 2020
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Raft: Recurrent all-pairs field transforms for optical flow
Zachary Teed and Jia Deng · 2020
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Nerf-pytorch
Lin Yen-Chen · 2020
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Mip-nerf: A multiscale representation for anti-aliasing neural radiance fields
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 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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Stereo radiance fields (srf): Learning view synthesis for sparse views of novel scenes
Julian Chibane, Aayush Bansal, Verica Lazova, and Gerard Pons-Moll · 2021
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Depth-supervised nerf: Fewer views and faster training for free
Kangle Deng, Andrew Liu, Jun-Yan Zhu, and Deva Ramanan · 2021
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Putting nerf on a diet: Semantically consistent few-shot view synthesis
Ajay Jain, Matthew Tancik, and Pieter Abbeel · 2021
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Codenerf: Disentangled neural radiance fields for object categories
Wonbong Jang and Lourdes Agapito · 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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Improving neural implicit surfaces geometry with patch warping
François Darmon, Bénédicte Bascle, Jean-Clément Devaux, Pascal Monasse, and Mathieu Aubry · 2022
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Stylizednerf: consistent 3d scene stylization as stylized nerf via 2d-3d mutual learning
Yi-Hua Huang, Yue He, Yu-Jie Yuan, Yu-Kun Lai, and Lin Gao · 2022
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Geonerf: Generalizing nerf with geometry priors
Mohammad Mahdi Johari, Yann Lepoittevin, and François Fleuret · 2022
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Infonerf: Ray entropy minimization for few-shot neural volume rendering
Mijeong Kim, Seonguk Seo, and Bohyung Han · 2022
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Efficient neural radiance fields for interactive free-viewpoint video
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Mine: Towards continuous depth mpi with nerf for novel view synthesis
Jiaxin Li, Zijian Feng, Qi She, Henghui Ding, Changhu Wang, and Gim Hee Lee · 2021
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Neural rays for occlusion-aware image-based rendering
Yuan Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, and Wenping Wang · 2021
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Regnerf: Regularizing neural radiance fields for view synthesis from sparse inputs
Michael Niemeyer, Jonathan T Barron, Ben Mildenhall, Mehdi SM Sajjadi, Andreas Geiger, and Noha Radwan · 2021
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Sharf: Shape-conditioned radiance fields from a single view
Konstantinos Rematas, Ricardo Martin-Brualla, and Vittorio Ferrari · 2021
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Pixelsynth: Generating a 3d-consistent experience from a single image
Chris Rockwell, David F Fouhey, and Justin Johnson · 2021
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Dense depth priors for neural radiance fields from sparse input views
Barbara Roessle, Jonathan T Barron, Ben Mildenhall, Pratul P Srinivasan, and Matthias Nießner · 2021
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Grf: Learning a general radiance field for 3d representation and rendering
Alex Trevithick and Bo Yang · 2021
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Haotong Lin, Sida Peng, Zhen Xu, Yunzhi Yan, Qing Shuai, Hujun Bao, and Xiaowei Zhou · 2022
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Neural rays for occlusion-aware image-based rendering
Yuan Liu, Sida Peng, Lingjie Liu, Qianqian Wang, Peng Wang, Christian Theobalt, Xiaowei Zhou, and Wenping Wang · 2022
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Doublefield: Bridging the neural surface and radiance fields for high-fidelity human reconstruction and rendering
Ruizhi Shao, Hongwen Zhang, He Zhang, Mingjia Chen, Yan-Pei Cao, Tao Yu, and Yebin Liu · 2022
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Sparf: Neural radiance fields from sparse and noisy poses
Prune Truong, Marie-Julie Rakotosaona, Fabian Manhardt, and Federico Tombari · 2022
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Point-nerf: Point-based neural radiance fields
Qiangeng Xu, Zexiang Xu, Julien Philip, Sai Bi, Zhixin Shu, Kalyan Sunkavalli, and Ulrich Neumann · 2022
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Ray priors through reprojection: Improving neural radiance fields for novel view extrapolation
Jian Zhang, Yuanqing Zhang, Huan Fu, Xiaowei Zhou, Bowen Cai, Jinchi Huang, Rongfei Jia, Binqiang Zhao, and Xing Tang · 2022
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Devnet: Self-supervised monocular depth learning via density volume construction
Kaichen Zhou, Lanqing Hong, Changhao Chen, Hang Xu, Chaoqiang Ye, Qingyong Hu, and Zhenguo Li · 2022
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Sparsenerf: Distilling depth ranking for few-shot novel view synthesis
Guangcong Wang, Zhaoxi Chen, Chen Change Loy, and Ziwei Liu · 2023
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