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# Nerfies

This is the repository that contains source code for the [Nerfies website](https://nerfies.github.io).

If you find Nerfies useful for your work please cite:
```
@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},
}
```

# Website License
<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.
292 changes: 292 additions & 0 deletions index.html
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<!DOCTYPE html>
<html xmlns="http://www.w3.org/1999/html">
<head>
<meta charset="utf-8">
<meta name="description"
content="An automatic method to remove hair from real portrait images.">
<meta name="keywords" content="Face editing, Hair editing, StyleGAN">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>HairMapper: Removing Hair from Portraits Using GANs</title>

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More Research
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<a class="navbar-item" href="https://onethousandwu.com/3DPortraitGAN.github.io/">
3DPortraitGAN
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<section class="hero">
<div class="hero-body">
<div class="container is-max-desktop">
<div class="columns is-centered">
<div class="column has-text-centered">
<h1 class="title is-2 publication-title"><span class="dnerf">HairMapper</span>: <br />Removing Hair from Portraits Using GANs</h1>
<div class="is-size-3 publication-conf">

<span><b>CVPR 2022</b></span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://onethousandwu.com/">Yiqian Wu</a><sup>1,2</sup>,</span>
<span class="author-block">
<a href="https://www.yongliangyang.net/">Yongliang Yang</a><sup>3</sup>,</span>
<span class="author-block">
<a href="http://www.cad.zju.edu.cn/home/jin/">Xiaogang Jin*</a><sup>1,2</sup>
</span>
</div>

<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>State Key Lab of CAD&CG, Zhejiang University,</span>
<span class="author-block"><sup>2</sup>ZJU-Tencent Game and Intelligent Graphics InnovationTechnology Joint Lab, </span>
<span class="author-block"><sup>3</sup>University of Bath</span>
</div>

<div class="column has-text-centered">
<div class="publication-links">
<!-- PDF Link. -->
<span class="link-block">
<a href="https://openaccess.thecvf.com/content/CVPR2022/html/Wu_HairMapper_Removing_Hair_From_Portraits_Using_GANs_CVPR_2022_paper.html"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fas fa-file-pdf"></i>
</span>
<span>Paper</span>
</a>
</span>
<!-- Video Link. -->
<span class="link-block">
<a href="http://www.cad.zju.edu.cn/home/jin/cvpr2022/demo.mp4"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-youtube"></i>
</span>
<span>Video</span>
</a>
</span>
<!-- Code Link. -->
<span class="link-block">
<a href="https://github.com/oneThousand1000/HairMapper"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="fab fa-github"></i>
</span>
<span>Code</span>
</a>
</span>
<!-- Dataset Link. -->
<span class="link-block">
<a href="https://github.com/oneThousand1000/non-hair-FFHQ"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="far fa-images"></i>
</span>
<span>Data</span>
</a>
</div>

</div>
</div>
</div>
</div>
</div>
</section>

<section class="hero teaser">
<div class="container is-max-desktop">
<div class="hero-body">
<figure class="image">
<img src="./static/images/teaser.png" alt="teaser">
</figure>
<h2 class="subtitle has-text-centered">
Given portrait images with their faces partially occluded by hair, our method is
able to generate portraits without hair while preserving facial identity. After
removing the effects of hair, the resulting portrait images can be well employed
in hair design by simply blending the clean face with some hairstyle templates
without the interference from existing hair. Our results can also benefit 3D
face reconstruction by using the clean face textures generated by our method
(rows 2 and 4) in contrast to the results of the original images (rows 1 and 3).
</h2>
</div>
</div>
</section>


<section class="section">
<div class="container is-max-desktop">
<!-- Abstract. -->
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<p>
Removing hair from portrait images is challenging due to the complex occlusions
between hair and face, as well as the lack of paired portrait data with/without
hair.
</p>
<p>
To this end, we present a dataset and a baseline method for removing hair from
portrait images using generative adversarial networks (GANs). Our core idea is
to train a fully connected network $HairMapper$ to find the direction of hair
removal in the latent space of StyleGAN for the training stage. We develop a new
separation boundary and diffuse method to generate paired training data for males,
and a novel ''female-male-bald'' pipeline for paired data of females.
</p>
<p>
Experiments show that our method can naturally deal with portrait images with
variations on gender, age, etc. We validate the superior performance of our
method by comparing it to state-of-the-art methods through extensive experiments
and user studies. We also demonstrate its applications in hair design and 3D
face reconstruction.
</p>
</div>
</div>
</div>
<!--/ Abstract. -->

<!-- Paper video. -->
<div class="columns is-centered has-text-centered">
<div class="column is-four-fifths">
<h2 class="title is-3">Video</h2>
<div class="publication-video">
<iframe src="https://www.youtube.com/embed/UNtgpphVR2w?rel=0&amp;showinfo=0"
frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div>
</div>
</div>
<!--/ Paper video. -->

<!-- Pipeline. -->

<div class="columns is-centered">
<div class="column is-full-width">
<h2 class="title is-3">Pipeline</h2>
<div class="content has-text-justified">
<p>
The pipeline of our HairMapper.</p>
<figure class="image">
<img src="./static/images/pipeline.png" alt="Pipeline">
</figure>
</div>
</div>



<!--/ Pipeline. -->


</div>
</section>



<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@InProceedings{Wu_2022_CVPR,
author = {Wu, Yiqian and Yang, Yong-Liang and Jin, Xiaogang},
title = {HairMapper: Removing Hair From Portraits Using GANs},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2022},
pages = {4227-4236}
}
</code></pre>
</div>
</section>


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<p>
This website is licensed under a <a rel="license"
href="http://creativecommons.org/licenses/by-sa/4.0/">Creative
Commons Attribution-ShareAlike 4.0 International License</a>.
</p>
<p>
This page is borrowed from <a href="https://github.com/nerfies/nerfies.github.io">source code</a>. We thank the author for sharing it.
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