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<title>Nerfies: Deformable Neural Radiance Fields</title>
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<h1 class="title is-1 publication-title">Nerfies: Deformable Neural Radiance Fields</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://keunhong.com" target="_blank">Keunhong Park</a><sup>1</sup>,</span>
<span class="author-block">
<a href="https://utkarshsinha.com" target="_blank">Utkarsh Sinha</a><sup>2</sup>,</span>
<span class="author-block">
<a href="https://jonbarron.info" target="_blank">Jonathan T. Barron</a><sup>2</sup>,
</span>
<span class="author-block">
<a href="http://sofienbouaziz.com" target="_blank">Sofien Bouaziz</a><sup>2</sup>,
</span>
<span class="author-block">
<a href="https://www.danbgoldman.com" target="_blank">Dan B Goldman</a><sup>2</sup>,
</span>
<span class="author-block">
<a href="https://homes.cs.washington.edu/~seitz/" target="_blank">Steven M. Seitz</a><sup>1,2</sup>,
</span>
<span class="author-block">
<a href="http://www.ricardomartinbrualla.com" target="_blank">Ricardo Martin-Brualla</a><sup>2</sup>
</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>University of Washington,</span>
<span class="author-block"><sup>2</sup>Google Research</span>
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<span>Paper</span>
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<span>arXiv</span>
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<span>Code</span>
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<span>Data</span>
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<h2 class="subtitle has-text-centered">
<span class="dnerf">Nerfies</span> turns selfie videos from your phone into
free-viewpoint
portraits.
</h2>
</div>
</div>
</section>
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<h2 class="title is-3">Abstract</h2>
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<p>
We present the first method capable of photorealistically reconstructing a non-rigidly
deforming scene using photos/videos captured casually from mobile phones.
</p>
<p>
Our approach augments neural radiance fields
(NeRF) by optimizing an
additional continuous volumetric deformation field that warps each observed point into a
canonical 5D NeRF.
We observe that these NeRF-like deformation fields are prone to local minima, and
propose a coarse-to-fine optimization method for coordinate-based models that allows for
more robust optimization.
By adapting principles from geometry processing and physical simulation to NeRF-like
models, we propose an elastic regularization of the deformation field that further
improves robustness.
</p>
<p>
We show that <span class="dnerf">Nerfies</span> can turn casually captured selfie
photos/videos into deformable NeRF
models that allow for photorealistic renderings of the subject from arbitrary
viewpoints, which we dub <i>"nerfies"</i>. We evaluate our method by collecting data
using a
rig with two mobile phones that take time-synchronized photos, yielding train/validation
images of the same pose at different viewpoints. We show that our method faithfully
reconstructs non-rigidly deforming scenes and reproduces unseen views with high
fidelity.
</p>
</div>
</div>
</div>
<!--/ Abstract. -->
<!-- Paper video. -->
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<h2 class="title is-3">Video</h2>
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<iframe src="https://www.youtube.com/embed/MrKrnHhk8IA?rel=0&showinfo=0"
frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
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<!-- Visual Effects. -->
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<h2 class="title is-3">Visual Effects</h2>
<p>
Using <i>nerfies</i> you can create fun visual effects. This Dolly zoom effect
would be impossible without nerfies since it would require going through a wall.
</p>
<video id="dollyzoom" autoplay controls muted loop playsinline height="100%">
<source src="./static/videos/dollyzoom-stacked.mp4"
type="video/mp4">
</video>
</div>
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<!--/ Visual Effects. -->
<!-- Matting. -->
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<h2 class="title is-3">Matting</h2>
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<p>
As a byproduct of our method, we can also solve the matting problem by ignoring
samples that fall outside of a bounding box during rendering.
</p>
<video id="matting-video" controls playsinline height="100%">
<source src="./static/videos/matting.mp4"
type="video/mp4">
</video>
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<!--/ Matting. -->
<!-- Animation. -->
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<h2 class="title is-3">Animation</h2>
<!-- Interpolating. -->
<h3 class="title is-4">Interpolating states</h3>
<div class="content has-text-justified">
<p>
We can also animate the scene by interpolating the deformation latent codes of two input
frames. Use the slider here to linearly interpolate between the left frame and the right
frame.
</p>
</div>
<div class="columns is-vcentered interpolation-panel">
<div class="column is-3 has-text-centered">
<img src="./static/images/interpolate_start.jpg"
class="interpolation-image"
alt="Interpolate start reference image."/>
<p>Start Frame</p>
</div>
<div class="column interpolation-video-column">
<div id="interpolation-image-wrapper">
Loading...
</div>
<input class="slider is-fullwidth is-large is-info"
id="interpolation-slider"
step="1" min="0" max="100" value="0" type="range">
</div>
<div class="column is-3 has-text-centered">
<img src="./static/images/interpolate_end.jpg"
class="interpolation-image"
alt="Interpolation end reference image."/>
<p class="is-bold">End Frame</p>
</div>
</div>
<br/>
<!--/ Interpolating. -->
<!-- Re-rendering. -->
<h3 class="title is-4">Re-rendering the input video</h3>
<div class="content has-text-justified">
<p>
Using <span class="dnerf">Nerfies</span>, you can re-render a video from a novel
viewpoint such as a stabilized camera by playing back the training deformations.
</p>
</div>
<div class="content has-text-centered">
<video id="replay-video"
controls
muted
preload
playsinline
width="75%">
<source src="./static/videos/replay.mp4"
type="video/mp4">
</video>
</div>
<!--/ Re-rendering. -->
</div>
</div>
<!--/ Animation. -->
<!-- Concurrent Work. -->
<div class="columns is-centered">
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<h2 class="title is-3">Related Links</h2>
<div class="content has-text-justified">
<p>
There's a lot of excellent work that was introduced around the same time as ours.
</p>
<p>
<a href="https://arxiv.org/abs/2104.09125" target="_blank">Progressive Encoding for Neural Optimization</a> introduces an idea similar to our windowed position encoding for coarse-to-fine optimization.
</p>
<p>
<a href="https://www.albertpumarola.com/research/D-NeRF/index.html" target="_blank">D-NeRF</a> and <a href="https://gvv.mpi-inf.mpg.de/projects/nonrigid_nerf/" target="_blank">NR-NeRF</a>
both use deformation fields to model non-rigid scenes.
</p>
<p>
Some works model videos with a NeRF by directly modulating the density, such as <a href="https://video-nerf.github.io/" target="_blank">Video-NeRF</a>, <a href="https://www.cs.cornell.edu/~zl548/NSFF/" target="_blank">NSFF</a>, and <a href="https://neural-3d-video.github.io/" target="_blank">DyNeRF</a>
</p>
<p>
There are probably many more by the time you are reading this. Check out <a href="https://dellaert.github.io/NeRF/" target="_blank">Frank Dellart's survey on recent NeRF papers</a>, and <a href="https://github.com/yenchenlin/awesome-NeRF" target="_blank">Yen-Chen Lin's curated list of NeRF papers</a>.
</p>
</div>
</div>
</div>
<!--/ Concurrent Work. -->
</div>
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@article{park2021nerfies,
author = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
title = {Nerfies: Deformable Neural Radiance Fields},
journal = {ICCV},
year = {2021},
}</code></pre>
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