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Representing and rendering dynamic scenes has been an important but challenging task.
Volume rendering
Robert A Drebin, Loren Carpenter, and Pat Hanrahan · 1988
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Surface splatting
Matthias Zwicker, Hanspeter Pfister, Jeroen Van Baar, and Markus Gross · 2001
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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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High-quality streamable free-viewpoint video
Alvaro Collet, Ming Chuang, Pat Sweeney, Don Gillett, Dennis Evseev, David Calabrese, Hugues Hoppe, Adam Kirk, and Steve Sullivan · 2015
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Robust non-rigid motion tracking and surface reconstruction using l0 regularization
Kaiwen Guo, Feng Xu, Yangang Wang, Yebin Liu, and Qionghai Dai · 2015
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Panoptic studio: A massively multiview system for social motion capture
Hanbyul Joo, Hao Liu, Lei Tan, Lin Gui, Bart Nabbe, Iain Matthews, Takeo Kanade, Shohei Nobuhara, and Yaser Sheikh · 2015
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Robust 3d human motion reconstruction via dynamic template construction
Zhong Li, Yu Ji, Wei Yang, Jinwei Ye, and Jingyi Yu · 2017
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4d human body correspondences from panoramic depth maps
Zhong Li, Minye Wu, Wangyiteng Zhou, and Jingyi Yu · 2018
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Pu-net: Point cloud upsampling network
Lequan Yu, Xianzhi Li, Chi-Wing Fu, Daniel Cohen-Or, and Pheng-Ann Heng · 2018
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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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Deepview: View synthesis with learned gradient descent
John Flynn, Michael Broxton, Paul Debevec, Matthew DuVall, Graham Fyffe, Ryan Overbeck, Noah Snavely, and Richard Tucker · 2019
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The relightables: Volumetric performance capture of humans with realistic relighting
Kaiwen Guo, Peter Lincoln, Philip Davidson, Jay Busch, Xueming Yu, Matt Whalen, Geoff Harvey, Sergio Orts-Escolano, Rohit Pandey, Jason Dourgarian, et al · 2019
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Meteornet: Deep learning on dynamic 3d point cloud sequences
Xingyu Liu, Mengyuan Yan, and Jeannette Bohg · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
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Differentiable surface splatting for point-based geometry processing
Wang Yifan, Felice Serena, Shihao Wu, Cengiz Öztireli, and Olga Sorkine-Hornung · 2019
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Immersive light field video with a layered mesh representation
Michael Broxton, John Flynn, Ryan Overbeck, Daniel Erickson, Peter Hedman, Matthew Duvall, Jason Dourgarian, Jay Busch, Matt Whalen, and Paul Debevec · 2020
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Robustfusion: Human volumetric capture with data-driven visual cues using a rgbd camera
Zhuo Su, Lan Xu, Zerong Zheng, Tao Yu, Yebin Liu, and Lu Fang · 2020
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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
Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
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Dynamic view synthesis from dynamic monocular video
Chen Gao, Ayush Saraf, Johannes Kopf, and Jia-Bin Huang · 2021
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Neural scene flow fields for space-time view synthesis of dynamic scenes
Zhengqi Li, Simon Niklaus, Noah Snavely, and Oliver Wang · 2021
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Nerf in the wild: Neural radiance fields for unconstrained photo collections
Ricardo Martin-Brualla, Noha Radwan, Mehdi SM Sajjadi, Jonathan T Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
Cited alongside, same era.
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 · 2021
Cited alongside, same era.
K-planes: Explicit radiance fields in space, time, and appearance
Sara Fridovich-Keil, Giacomo Meanti, Frederik Rahbæk Warburg, Benjamin Recht, and Angjoo Kanazawa · 2023
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V4d: Voxel for 4d novel view synthesis
Wanshui Gan, Hongbin Xu, Yi Huang, Shifeng Chen, and Naoto Yokoya · 2023
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Forward flow for novel view synthesis of dynamic scenes
Xiang Guo, Jiadai Sun, Yuchao Dai, Guanying Chen, Xiaoqing Ye, Xiao Tan, Errui Ding, Yumeng Zhang, and Jingdong Wang · 2023
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3d gaussian splatting for real-time radiance field rendering
Bernhard Kerbl, Georgios Kopanas, Thomas Leimkühler, and George Drettakis · 2023
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Flexible techniques for differentiable rendering with 3d gaussians
Leonid Keselman and Martial Hebert · 2023
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Spacetime gaussian feature splatting for real-time dynamic view synthesis
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Albert Pumarola, Enric Corona, Gerard Pons-Moll, and Francesc Moreno-Noguer · 2021
Cited alongside, same era.
Ibrnet: Learning multi-view image-based rendering
Qianqian Wang, Zhicheng Wang, Kyle Genova, Pratul P Srinivasan, Howard Zhou, Jonathan T Barron, Ricardo Martin-Brualla, Noah Snavely, and Thomas Funkhouser · 2021
Cited alongside, same era.
Particlenerf: Particle based encoding for online neural radiance fields in dynamic scenes
Jad Abou-Chakra, Feras Dayoub, and Niko Sünderhauf · 2022
Cited alongside, same era.
Fast dynamic radiance fields with time-aware neural voxels
Jiemin Fang, Taoran Yi, Xinggang Wang, Lingxi Xie, Xiaopeng Zhang, Wenyu Liu, Matthias Nießner, and Qi Tian · 2022
Cited alongside, same era.
Plenoxels: Radiance fields without neural networks
Sara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa · 2022
Cited alongside, same era.
Hvtr: Hybrid volumetric-textural rendering for human avatars
Tao Hu, Tao Yu, Zerong Zheng, He Zhang, Yebin Liu, and Matthias Zwicker · 2022
Cited alongside, same era.
Approximate differentiable rendering with algebraic surfaces
Leonid Keselman and Martial Hebert · 2022
Cited alongside, same era.
Zhan Li, Zhang Chen, Zhong Li, and Yi Xu · 2023
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High-fidelity and real-time novel view synthesis for dynamic scenes
Haotong Lin, Sida Peng, Zhen Xu, Tao Xie, Xingyi He, Hujun Bao, and Xiaowei Zhou · 2023
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Robust dynamic radiance fields
Yu-Lun Liu, Chen Gao, Andreas Meuleman, Hung-Yu Tseng, Ayush Saraf, Changil Kim, Yung-Yu Chuang, Johannes Kopf, and Jia-Bin Huang · 2023
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Representing volumetric videos as dynamic mlp maps
Sida Peng, Yunzhi Yan, Qing Shuai, Hujun Bao, and Xiaowei Zhou · 2023
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Tensor4d: Efficient neural 4d decomposition for high-fidelity dynamic reconstruction and rendering
Ruizhi Shao, Zerong Zheng, Hanzhang Tu, Boning Liu, Hongwen Zhang, and Yebin Liu · 2023
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Nerfplayer: A streamable dynamic scene representation with decomposed neural radiance fields
Liangchen Song, Anpei Chen, Zhong Li, Zhang Chen, Lele Chen, Junsong Yuan, Yi Xu, and Andreas Geiger · 2023
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Mononerf: Learning a generalizable dynamic radiance field from monocular videos
Fengrui Tian, Shaoyi Du, and Yueqi Duan · 2023
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Generalizable neural voxels for fast human radiance fields
Taoran Yi, Jiemin Fang, Xinggang Wang, and Wenyu Liu · 2023
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A survey on 3d gaussian splatting
Guikun Chen and Wenguan Wang · 2024
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Dynamic 3d gaussians: Tracking by persistent dynamic view synthesis
Jonathon Luiten, Georgios Kopanas, Bastian Leibe, and Deva Ramanan · 2024
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Point-dynrf: Point-based dynamic radiance fields from a monocular video
Byeongjun Park and Changick Kim · 2024
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Dynpoint: Dynamic neural point for view synthesis
Kaichen Zhou, Jia-Xing Zhong, Sangyun Shin, Kai Lu, Yiyuan Yang, Andrew Markham, and Niki Trigoni · 2024
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