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<li class="toctree-l1"><a class="reference internal" href="../../quickstart/installation.html">Installation</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../quickstart/first_nerf.html">Training your first model</a></li>
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<p class="caption" role="heading"><span class="caption-text">Extensions</span></p>
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<ul>
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<li class="toctree-l1"><a class="reference internal" href="../../extensions/blender_addon.html">Blender VFX add-on</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../extensions/unreal_engine.html">Exporting to Unreal Engine</a></li>
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<li class="toctree-l1"><a class="reference internal" href="../../extensions/sdfstudio.html">SDFStudio</a></li>
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</ul>
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<p class="caption" role="heading"><span class="caption-text">NeRFology</span></p>
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<li class="toctree-l2"><a class="reference internal" href="instant_ngp.html"> Instant-NGP</a></li>
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<li class="toctree-l2 current current-page"><a class="current reference internal" href="#"> Splatfacto</a></li>
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<li class="toctree-l2"><a class="reference internal" href="in2n.html"> Instruct-NeRF2NeRF</a></li>
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<li class="toctree-l2"><a class="reference internal" href="signerf.html"> SIGNeRF</a></li>
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<li class="toctree-l2"><a class="reference internal" href="kplanes.html"> K-Planes</a></li>
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<li class="toctree-l2"><a class="reference internal" href="lerf.html"> LERF</a></li>
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<li class="toctree-l2"><a class="reference internal" href="feature_splatting.html"> Feature-Splatting</a></li>
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<li class="toctree-l2"><a class="reference internal" href="mipnerf.html"> Mip-NeRF</a></li>
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<li class="toctree-l2"><a class="reference internal" href="nerf.html"> NeRF</a></li>
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<li class="toctree-l2"><a class="reference internal" href="nerfacto.html"> Nerfacto</a></li>
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<li class="toctree-l2"><a class="reference internal" href="nerfbusters.html"> Nerfbusters</a></li>
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<li class="toctree-l2"><a class="reference internal" href="tetranerf.html"> Tetra-NeRF</a></li>
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<li class="toctree-l2"><a class="reference internal" href="tensorf.html"> TensoRF</a></li>
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<article role="main">
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<section class="tex2jax_ignore mathjax_ignore" id="splatfacto">
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<h1>Splatfacto<a class="headerlink" href="#splatfacto" title="Permalink to this heading">#</a></h1>
|
||
<h4>Nerfstudio's Gaussian Splatting Implementation</h4>
|
||
<iframe width="560" height="315" src="https://www.youtube.com/embed/0yueTFx-MdQ?si=GxiYnFAeYVVl-soJ" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowfullscreen></iframe>
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<p><a class="sd-sphinx-override sd-btn sd-text-wrap sd-btn-outline-primary reference external" href="https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/"><span>Paper Website</span></a></p>
|
||
<p><a class="reference external" href="https://repo-sam.inria.fr/fungraph/3d-gaussian-splatting/">3D Gaussian Splatting</a> was proposed in SIGGRAPH 2023 from INRIA, and is a completely different method of representing radiance fields by explicitly storing a collection of 3D volumetric gaussians. These can be “splatted”, or projected, onto a 2D image provided a camera pose, and rasterized to obtain per-pixel colors. Because rasterization is very fast on GPUs, this method can render much faster than neural representations of radiance fields.</p>
|
||
<p>To avoid confusion with the original paper, we refer to nerfstudio’s implementation as “Splatfacto”, which will drift away from the original as more features are added. Just as Nerfacto is a blend of various different methods, Splatfacto will be a blend of different gaussian splatting methodologies.</p>
|
||
<section id="installation">
|
||
<h2>Installation<a class="headerlink" href="#installation" title="Permalink to this heading">#</a></h2>
|
||
<p><a class="sd-sphinx-override sd-btn sd-text-wrap sd-btn-outline-primary reference external" href="https://docs.gsplat.studio/"><span>GSplat </span></a></p>
|
||
<p>Nerfstudio uses <a class="reference external" href="https://github.com/nerfstudio-project/gsplat">gsplat</a> as its gaussian rasterization backend, an in-house re-implementation which is designed to be more developer friendly. This can be installed with <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">gsplat</span></code>. The associated CUDA code will be compiled the first time gsplat is executed. Some users with PyTorch 2.0 have experienced issues with this, which can be resolved by either installing gsplat from source, or upgrading torch to 2.1.</p>
|
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</section>
|
||
<section id="data">
|
||
<h2>Data<a class="headerlink" href="#data" title="Permalink to this heading">#</a></h2>
|
||
<p>Gaussian splatting works much better if you initialize it from pre-existing geometry, such as SfM points from COLMAP. COLMAP datasets or datasets from <code class="docutils literal notranslate"><span class="pre">ns-process-data</span></code> will automatically save these points and initialize gaussians on them. Other datasets currently do not support initialization, and will initialize gaussians randomly. Initializing from other data inputs (i.e. depth from phone app scanners) may be supported in the future.</p>
|
||
<p>Because the method trains on <em>full images</em> instead of bundles of rays, there is a new datamanager in <code class="docutils literal notranslate"><span class="pre">full_images_datamanager.py</span></code> which undistorts input images, caches them, and provides single images at each train step.</p>
|
||
</section>
|
||
<section id="running-the-method">
|
||
<h2>Running the Method<a class="headerlink" href="#running-the-method" title="Permalink to this heading">#</a></h2>
|
||
<p>To run splatfacto, run <code class="docutils literal notranslate"><span class="pre">ns-train</span> <span class="pre">splatfacto</span> <span class="pre">--data</span> <span class="pre"><data></span></code>. Just like NeRF methods, the splat can be interactively viewed in the web-viewer, loaded from a checkpoint, rendered, and exported.</p>
|
||
<p>We provide a few additional variants:</p>
|
||
<div class="table-wrapper colwidths-auto docutils container">
|
||
<table class="docutils align-default">
|
||
<thead>
|
||
<tr class="row-odd"><th class="head"><p>Method</p></th>
|
||
<th class="head"><p>Description</p></th>
|
||
<th class="head"><p>Memory</p></th>
|
||
<th class="head"><p>Speed</p></th>
|
||
</tr>
|
||
</thead>
|
||
<tbody>
|
||
<tr class="row-even"><td><p><code class="docutils literal notranslate"><span class="pre">splatfacto</span></code></p></td>
|
||
<td><p>Default Model</p></td>
|
||
<td><p>~6GB</p></td>
|
||
<td><p>Fast</p></td>
|
||
</tr>
|
||
<tr class="row-odd"><td><p><code class="docutils literal notranslate"><span class="pre">splatfacto-big</span></code></p></td>
|
||
<td><p>More Gaussians, Higher Quality</p></td>
|
||
<td><p>~12GB</p></td>
|
||
<td><p>Slower</p></td>
|
||
</tr>
|
||
</tbody>
|
||
</table>
|
||
</div>
|
||
<p>A full evalaution of Nerfstudio’s implementation of Gaussian Splatting against the original Inria method can be found <a class="reference external" href="https://docs.gsplat.studio/main/tests/eval.html">here</a>.</p>
|
||
<section id="quality-and-regularization">
|
||
<h3>Quality and Regularization<a class="headerlink" href="#quality-and-regularization" title="Permalink to this heading">#</a></h3>
|
||
<p>The default settings provided maintain a balance between speed, quality, and splat file size, but if you care more about quality than training speed or size, you can decrease the alpha cull threshold
|
||
(threshold to delete translucent gaussians) and disable culling after 15k steps like so: <code class="docutils literal notranslate"><span class="pre">ns-train</span> <span class="pre">splatfacto</span> <span class="pre">--pipeline.model.cull_alpha_thresh=0.005</span> <span class="pre">--pipeline.model.continue_cull_post_densification=False</span> <span class="pre">--data</span> <span class="pre"><data></span></code></p>
|
||
<p>A common artifact in splatting is long, spikey gaussians. <a class="reference external" href="https://xpandora.github.io/PhysGaussian/">PhysGaussian</a> proposes a scale regularizer that encourages gaussians to be more evenly shaped. To enable this, set the <code class="docutils literal notranslate"><span class="pre">pipeline.model.use_scale_regularization</span></code> flag to <code class="docutils literal notranslate"><span class="pre">True</span></code>.</p>
|
||
</section>
|
||
</section>
|
||
<section id="details">
|
||
<h2>Details<a class="headerlink" href="#details" title="Permalink to this heading">#</a></h2>
|
||
<p>For more details on the method, see the <a class="reference external" href="https://arxiv.org/abs/2308.04079">original paper</a>. Additionally, for a detailed derivation of the gradients used in the gsplat library, see <a class="reference external" href="https://arxiv.org/abs/2312.02121">here</a>.</p>
|
||
</section>
|
||
<section id="exporting-splats">
|
||
<h2>Exporting splats<a class="headerlink" href="#exporting-splats" title="Permalink to this heading">#</a></h2>
|
||
<p>Gaussian splats can be exported as a <code class="docutils literal notranslate"><span class="pre">.ply</span></code> file which are ingestable by a variety of online web viewers. You can do this via the viewer, or <code class="docutils literal notranslate"><span class="pre">ns-export</span> <span class="pre">gaussian-splat</span> <span class="pre">--load-config</span> <span class="pre"><config></span> <span class="pre">--output-dir</span> <span class="pre">exports/splat</span></code>. Currently splats can only be exported from trained splats, not from nerfacto.</p>
|
||
<p>Nerfstudio’s splat export currently supports multiple third-party splat viewers:</p>
|
||
<ul class="simple">
|
||
<li><p><a class="reference external" href="https://poly.cam/tools/gaussian-splatting">Polycam Viewer</a></p></li>
|
||
<li><p><a class="reference external" href="https://playcanvas.com/super-splat">Playcanvas SuperSplat</a></p></li>
|
||
<li><p><a class="reference external" href="https://antimatter15.com/splat/">WebGL Viewer by antimatter15</a></p></li>
|
||
<li><p><a class="reference external" href="https://spline.design/">Spline</a></p></li>
|
||
<li><p><a class="reference external" href="https://github.com/mkkellogg/GaussianSplats3D">Three.js Viewer by mkkellogg</a></p></li>
|
||
</ul>
|
||
</section>
|
||
<section id="faq">
|
||
<h2>FAQ<a class="headerlink" href="#faq" title="Permalink to this heading">#</a></h2>
|
||
<ul class="simple">
|
||
<li><p>Can I export a mesh or pointcloud?</p></li>
|
||
</ul>
|
||
<p>Currently these export options are not supported, but may be in the future. Contributions are always welcome!</p>
|
||
<ul class="simple">
|
||
<li><p>Can I render fisheye, equirectangular, orthographic images?</p></li>
|
||
</ul>
|
||
<p>Currently, no. Gaussian rasterization assumes a perspective camera for its rasterization pipeline. Implementing other camera models is of interest but not currently planned.</p>
|
||
</section>
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</section>
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<div class="title">Splatfacto in the Wild</div>
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<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
|
||
</a>
|
||
<a class="prev-page" href="instant_ngp.html">
|
||
<svg class="furo-related-icon"><use href="#svg-arrow-right"></use></svg>
|
||
<div class="page-info">
|
||
<div class="context">
|
||
<span>Previous</span>
|
||
</div>
|
||
|
||
<div class="title">Instant-NGP</div>
|
||
|
||
</div>
|
||
</a>
|
||
</div>
|
||
<div class="bottom-of-page">
|
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<div class="left-details">
|
||
<div class="copyright">
|
||
Copyright © 2022, nerfstudio Team
|
||
</div>
|
||
Made with <a href="https://www.sphinx-doc.org/">Sphinx</a> and <a class="muted-link" href="https://pradyunsg.me">@pradyunsg</a>'s
|
||
|
||
<a href="https://github.com/pradyunsg/furo">Furo</a>
|
||
|
||
</div>
|
||
<div class="right-details">
|
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<div class="icons">
|
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|
||
</div>
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</div>
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</div>
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</footer>
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</div>
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<aside class="toc-drawer">
|
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|
||
|
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<div class="toc-sticky toc-scroll">
|
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<div class="toc-title-container">
|
||
<span class="toc-title">
|
||
On this page
|
||
</span>
|
||
</div>
|
||
<div class="toc-tree-container">
|
||
<div class="toc-tree">
|
||
<ul>
|
||
<li><a class="reference internal" href="#">Splatfacto</a><ul>
|
||
<li><a class="reference internal" href="#installation">Installation</a></li>
|
||
<li><a class="reference internal" href="#data">Data</a></li>
|
||
<li><a class="reference internal" href="#running-the-method">Running the Method</a><ul>
|
||
<li><a class="reference internal" href="#quality-and-regularization">Quality and Regularization</a></li>
|
||
</ul>
|
||
</li>
|
||
<li><a class="reference internal" href="#details">Details</a></li>
|
||
<li><a class="reference internal" href="#exporting-splats">Exporting splats</a></li>
|
||
<li><a class="reference internal" href="#faq">FAQ</a></li>
|
||
</ul>
|
||
</li>
|
||
</ul>
|
||
|
||
</div>
|
||
</div>
|
||
</div>
|
||
|
||
|
||
</aside>
|
||
</div>
|
||
</div></body>
|
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|
||
</html> |