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We propose NEMTO, the first end-to-end neural rendering pipeline to model 3D transparent objects with complex geometry and unknown indices of refraction.
The rendering equation
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Douglas E Zongker, Dawn M Werner, Brian Curless, and David H Salesin · 1999
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Yung-Yu Chuang, Douglas E Zongker, Joel Hindorff, Brian Curless, David H Salesin, and Richard Szeliski · 2000
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Cong Phuoc Huynh, Antonio Robles-Kelly, and Edwin Hancock · 2010
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Gordon Wetzstein, David Roodnick, Wolfgang Heidrich, and Ramesh Raskar · 2011
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Matt Pharr, Wenzel Jakob, and Greg Humphreys · 2016
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Zhaopeng Cui, Jinwei Gu, Boxin Shi, Ping Tan, and Jan Kautz · 2017
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Acquiring axially-symmetric transparent objects using single-view transmission imaging
Jaewon Kim, Ilya Reshetouski, and Abhijeet Ghosh · 2017
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Guanying Chen, Kai Han, and Kwan-Yee K Wong · 2018
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Bojian Wu, Yang Zhou, Yiming Qian, Minglun Cong, and Hui Huang · 2018
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Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Ricardo Martin-Brualla, Noha Radwan, Mehdi SM Sajjadi, Jonathan T Barron, Alexey Dosovitskiy, and Daniel Duckworth · 2021
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Volume rendering of neural implicit surfaces
Lior Yariv, Jiatao Gu, Yoni Kasten, and Yaron Lipman · 2021
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Physg: Inverse rendering with spherical gaussians for physics-based material editing and relighting
Kai Zhang, Fujun Luan, Qianqian Wang, Kavita Bala, and Noah Snavely · 2021
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Xiuming Zhang, Pratul P Srinivasan, Boyang Deng, Paul Debevec, William T Freeman, and Jonathan T Barron · 2021
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Jonathan T. Barron, Ben Mildenhall, Dor Verbin, Pratul P. Srinivasan, and Peter Hedman · 2022
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A hybrid mesh-neural representation for 3d transparent object reconstruction
Jiamin Xu, Zihan Zhu, Hujun Bao, and Wewei Xu · 2023
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