| | ---
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| | license: cc-by-nc-sa-4.0
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| | tags:
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| | - audio-visual-learning
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| | - neural-radiance-fields
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| | - neural-acoustic-fields
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| | - spatial-audio
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| | - nerfstudio
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| | - pytorch
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| | datasets:
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| | - RAF
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| | - SoundSpaces
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| | ---
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| |
|
| | Official pretrained model weights for NeRAF from the paper: **"NeRAF: 3D Scene Infused Neural Radiance and Acoustic Fields"** (ICLR 2025).
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| |
|
| | This repository contains pretrained checkpoints for RAF dataset and 6 SoundSpaces scenes.
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| |
|
| | For training, evaluation, and usage instructions please see the official codebase:
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| | 👉 https://github.com/AmandineBtto/NeRAF
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| |
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| |
|
| | You can download all weights using:
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| |
|
| | ```bash
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| | huggingface-cli download AmandineBtto/NeRAF --local-dir weights/NeRAF
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| | ```
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| |
|
| | If you use these weights, please cite:
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| |
|
| | ```
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| | @inproceedings{
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| | brunetto2025neraf,
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| | title={Ne{RAF}: 3D Scene Infused Neural Radiance and Acoustic Fields},
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| | author={Amandine Brunetto and Sascha Hornauer and Fabien Moutarde},
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| | booktitle={The Thirteenth International Conference on Learning Representations},
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| | year={2025},
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| | url={https://openreview.net/forum?id=njvSBvtiwp}
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| | }
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| | ``` |
