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In this paper, we propose \textit{binary radiance fields} (BiRF), a storage-efficient radiance field representation employing binary feature encoding that encodes local features using binary encoding parameters in a format of either $+1$ or $-1$.
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Ben Mildenhall, Pratul P Srinivasan, Matthew Tancik, Jonathan T Barron, Ravi Ramamoorthi, and Ren Ng · 2021
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Keunhong Park, Utkarsh Sinha, Peter Hedman, Jonathan T Barron, Sofien Bouaziz, Dan B Goldman, Ricardo Martin-Brualla, and Steven M Seitz · 2021
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Alex Yu, Vickie Ye, Matthew Tancik, and Angjoo Kanazawa · 2021
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Alex Yu, Ruilong Li, Matthew Tancik, Hao Li, Ren Ng, and Angjoo Kanazawa · 2021
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Jonathan T Barron, Ben Mildenhall, Matthew Tancik, Peter Hedman, Ricardo Martin-Brualla, and Pratul P Srinivasan · 2021
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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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Zirui Wang, Shangzhe Wu, Weidi Xie, Min Chen, and Victor Adrian Prisacariu · 2021
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Christian Reiser, Songyou Peng, Yiyi Liao, and Andreas Geiger · 2021
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Variable bitrate neural fields
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Michael Niemeyer, Jonathan T Barron, Ben Mildenhall, Mehdi SM Sajjadi, Andreas Geiger, and Noha Radwan · 2022
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Cheng Sun, Min Sun, and Hwann-Tzong Chen · 2022
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Sara Fridovich-Keil, Alex Yu, Matthew Tancik, Qinhong Chen, Benjamin Recht, and Angjoo Kanazawa · 2022
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Efficient geometry-aware 3d generative adversarial networks
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Scalable neural video representations with learnable positional features
Subin Kim, Sihyun Yu, Jaeho Lee, and Jinwoo Shin · 2022
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Ruilong Li, Matthew Tancik, and Angjoo Kanazawa · 2022
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