README.md

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).