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[EventNeRF](https://4dqv.mpi-inf.mpg.de/EventNeRF/)\n[Viktor Rudnev](https://twitter.com/realr00tman), [Mohamed Elgharib](https://people.mpi-inf.mpg.de/~elgharib/), [Christian Theobalt](https://www.mpi-inf.mpg.de/~theobalt/), [Vladislav Golyanik](https://people.mpi-inf.mpg.de/~golyanik/)\n\n![EventNeRF: Neural Radiance Fields from a Single Colour Event Camera](demo/EventNeRF.gif)\n\nBased on [NeRF-OSR codebase](https://github.com/r00tman/NeRF-OSR), which is based on [NeRF++ codebase](https://github.com/Kai-46/nerfplusplus) and inherits the same training data preprocessing and format.\n\n## Data\n\nDownload the datasets from [here](https://nextcloud.mpi-klsb.mpg.de/index.php/s/xDqwRHiWKeSRyes).\n\nUntar the downloaded archive into `data/` sub-folder in the code directory.\n\nSee NeRF++ sections on [data](https://github.com/Kai-46/nerfplusplus#data) and [COLMAP](https://github.com/Kai-46/nerfplusplus#generate-camera-parameters-intrinsics-and-poses-with-colmap-sfm) on how to create adapt a new dataset for training. \n\nPlease contact us if you need to adapt your own event stream as it might need updates to the code.\n\n## Create environment\n\n```\nconda env create --file environment.yml\nconda activate eventnerf\n```\n\n## Training and Testing\n\nUse the scripts from `scripts/` subfolder for training and testing.\nPlease replace `\u003cabsolute-path-to-code\u003e` and `\u003cpath-to-conda-env\u003e` in the `.sh` scripts and the corresponding `.txt` config file\nTo do so automatically for all of the files, you can use `sed`:\n```\nsed 's/\u003cabsolute-path-to-code\u003e/\\/your\\/path/' configs/**/*.txt scripts/*.sh\nsed 's/\u003cpath-to-conda-env\u003e/\\/your\\/path/' scripts/*.sh\n```\n\n## Models\n\n - `configs/nerf/*`, `configs/lego1/*` -- synthetic data,\n - `configs/nextgen/*`, `configs/nextnextgen/*` -- real data (from the revised paper),\n - `configs/ablation/*` -- ablation studies,\n - `configs/altbase.txt` -- constant window length baseline,\n - `configs/angle/*` -- camera angle error robustness ablation,\n - `configs/noise/*` -- noise events robustness ablation,\n - `configs/deff/*` -- data efficiency ablation (varying amount of data by varying the simulated event threshold),\n - `configs/e2vid/*` -- synthetic data e2vid baseline,\n - `configs/real/*` -- real data (from the old version of the paper)\n\n## Mesh Extraction\n\nTo extract the mesh from a trained model, run\n\n```\nddp_mesh_nerf.py --config nerf/chair.txt\n```\n\nReplace `nerf/chair.txt` with the path to your trained model config.\n\n\n## Evaluation\nPlease find the guide on evaluation, color-correction, and computing the metrics in [`metric/README.md`](https://github.com/r00tman/EventNeRF/blob/main/metric/README.md).\n\n## Citation\n\nPlease cite our work if you use the code.\n\n```\n@InProceedings{rudnev2023eventnerf,\n      title={EventNeRF: Neural Radiance Fields from a Single Colour Event Camera},\n      author={Viktor Rudnev and Mohamed Elgharib and Christian Theobalt and Vladislav Golyanik},\n      booktitle={Computer Vision and Pattern Recognition (CVPR)},\n      year={2023}\n}\n```\n\n## License\n\nThis work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. To view a copy of this license, visit [http://creativecommons.org/licenses/by-nc-sa/4.0/](http://creativecommons.org/licenses/by-nc-sa/4.0/) or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fr00tman%2Feventnerf","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fr00tman%2Feventnerf","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fr00tman%2Feventnerf/lists"}