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FPO++: Efficient Encoding and Rendering of Dynamic Neural Radiance Fields by Analyzing and Enhancing Fourier PlenOctrees
Saskia Rabich · Patrick Stotko · Reinhard Klein
University of Bonn
The Visual Computer · Presented at CGI 2024
Paper | arXiv | Project Page | Code
This repository contains data used in "FPO++: Efficient Encoding and Rendering of Dynamic Neural Radiance Fields by Analyzing and Enhancing Fourier PlenOctrees".
Usage
You can use this data by downloading and extracting the .zip-files into a data
subdirectory in the root directory of the FPO++ source code.
Please refer to the GitHub repository for information on how to run the code.
Citation
If you find this data useful for your research, please cite FPO++ as follows:
@article{rabich2024FPOplusplus:,
title = {FPO++: efficient encoding and rendering of dynamic neural radiance fields by analyzing and enhancing {Fourier} {PlenOctrees}},
author = {Saskia Rabich and Patrick Stotko and Reinhard Klein},
journal = {The Visual Computer},
year = {2024},
issn = {1432-2315},
doi = {10.1007/s00371-024-03475-3},
url = {https://doi.org/10.1007/s00371-024-03475-3},
}
License
This data is provided under the MIT license.
Acknowledgements
This work has been funded by the Federal Ministry of Education and Research under grant no. 01IS22094E WEST-AI, by the Federal Ministry of Education and Research of Germany and the state of North-Rhine Westphalia as part of the Lamarr-Institute for Machine Learning and Artificial Intelligence, and additionally by the DFG project KL 1142/11-2 (DFG Research Unit FOR 2535 Anticipating Human Behavior).
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