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33 lines
1.2 KiB
Markdown
33 lines
1.2 KiB
Markdown
# Zip-NeRF
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<h4>A pytorch implementation of "Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields"</h4>
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```{button-link} https://jonbarron.info/zipnerf/
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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/SuLvXiangXin/zipnerf-pytorch
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:color: primary
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:outline:
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Code
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```
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### Installation
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First, install nerfstudio and its dependencies. Then run:
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```
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pip install git+https://github.com/SuLvXiangXin/zipnerf-pytorch#subdirectory=extensions/cuda
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pip install git+https://github.com/SuLvXiangXin/zipnerf-pytorch
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```
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Finally, install torch_scatter corresponding to your cuda version(https://pytorch-geometric.com/whl/torch-2.0.1%2Bcu118.html).
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### Running Model
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```bash
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ns-train zipnerf --data {DATA_DIR/SCENE}
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```
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## Overview
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Zipnerf combines mip-NeRF 360’s overall framework with iNGP’s featurization approach.
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Following mip-NeRF, zipnerf assume each pixel corresponds to a cone. Given an interval along the ray, it construct a set of multisamples that approximate the shape of that conical frustum.
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Also, it present an alternative loss that, unlike mip-NeRF 360’s interlevel loss, is continuous and smooth with respect to distance along the ray to prevent z-aliasing. |