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50 lines
1.8 KiB
Markdown
50 lines
1.8 KiB
Markdown
# NeRFPlayer
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<h4>A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fields</h4>
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```{button-link} https://lsongx.github.io/projects/nerfplayer.html
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:color: primary
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:outline:
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Paper Website
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```
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```{button-link} https://github.com/lsongx/nerfplayer-nerfstudio
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:color: primary
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:outline:
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Nerfstudio add-on code
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```
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[](https://www.youtube.com/watch?v=flVqSLZWBMI)
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## Installation
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First install nerfstudio dependencies. Then run:
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```bash
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pip install git+https://github.com/lsongx/nerfplayer-nerfstudio.git
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```
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## Running NeRFPlayer
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Details for running NeRFPlayer can be found [here](https://github.com/lsongx/nerfplayer-nerfstudio). Once installed, run:
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```bash
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ns-train nerfplayer-ngp --help
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```
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Two variants of NeRFPlayer are provided:
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| Method | Description |
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| --------------------- | ----------------------------------------------- |
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| `nerfplayer-nerfacto` | NeRFPlayer with nerfacto backbone |
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| `nerfplayer-ngp` | NeRFPlayer with instant-ngp-bounded backbone |
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## Method Overview
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<br>
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First, we propose to decompose the 4D spatiotemporal space according to temporal characteristics. Points in the 4D space are associated with probabilities of belonging to three categories: static, deforming, and new areas. Each area is represented and regularized by a separate neural field. Second, we propose a hybrid representations based feature streaming scheme for efficiently modeling the neural fields.
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Please see [TODO lists](https://github.com/lsongx/nerfplayer-nerfstudio#known-todos) to see the unimplemented components in the nerfstudio based version. |