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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<meta name="description" content="RePaint-NeRF.">
<meta name="keywords"
content="NeRF, Inpainting, Segmentation, SDS, LPIPS, Multli-View Inpainting, View Consistency, 3D Reconstruction, dreamfusion">
<meta name="viewport" content="width=device-width, initial-scale=1">
<title>RePaint-NeRF</title>
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</head>
<body>
<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-1 publication-title text-muted">
<!-- <span class="text-primary">߷</span> -->
<span class="text-dark">RePaint-NeRF</span>: NeRF Editting via Semantic Masks
and Diffusion Models
</h1>
<p class="is-size-5 text-center">
IJCAI 2023
</p>
<!-- <p class="is-size-5 text-center">
arXiv
</p> -->
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://scholar.google.com/citations?hl=zh-CN&user=t39WvtUAAAAJ">Xingchen
Zhou</a><sup>1,2</sup>,</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=wSdlXDYAAAAJ&hl=zh-CN&oi=ao">Ying
He</a><sup>1,2</sup>,</span>
<span class="author-block">
<a href="https://scholar.google.com/citations?user=zuGMGBoAAAAJ&hl=zh-CN&oi=sra">F
Richard
Yu</a><sup>1,2</sup>,
</span>
<span class="author-block">
Jianqiang
Li<sup>1,3</sup>,
</span>
<span class="author-block">
You
Li<sup>2</sup>,
</span>
</div>
<div class="is-size-6 publication-authors">
<span class="author-block text-muted">[email protected],</span>
<span class="author-block text-muted">{heying, yufei, lijq}@szu.edu.cn,</span>
<span class="author-block text-muted">[email protected]</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>College of Computer Science and Software Engineering,
Shenzhen University,</span>
<span class="author-block"><sup>2</sup>Guangdong Laboratory of Artificial Intelligence and
Digital Economy (SZ)</span>
<span class="author-block"><sup>3</sup>National Engineering Laboratory for Big Data System
Computing Technology, Shenzhen University</span>
<!-- </br>
<span class="author-block"><sup>*</sup>Denotes equal contribution</span> -->
</div>
<div class="column has-text-centered">
<div class="publication-links">
<span class="link-block">
<a href="https://arxiv.org/abs/2306.05668"
class="external-link button is-normal is-rounded is-dark">
<span class="icon">
<i class="ai ai-arxiv"></i>
</span>
<span>arXiv</span>
</a>
</span>
<!-- <span class="link-block">
<a href="paper.pdf"
class="external-link button is-normal is-rounded is-dark">
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<i class="fas fa-file-pdf"></i>
</span>
<span>Paper (High-Quality)</span>
</a>
</span> -->
<!-- <span class="link-block">
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class="external-link button is-normal is-rounded is-dark">
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<i class="fab fa-youtube"></i>
</span>
<span>Video</span>
</a>
</span> -->
<span class="link-block">
<a href="https://github.com/StarsTesla/RePaint-NeRF"
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>
</div>
</div>
</div>
</div>
</div>
</section>
<!-- Abstract -->
<section class="section">
<div class="container is-max-desktop">
<!-- Abstract. -->
<div class="columns is-centered has-text-centered">
<div class="column is-full">
<h2 class="title is-3">Abstract</h2>
<div class="content has-text-justified">
<!-- <img src="data/images/ov9.png" style="float: right; margin-left:20px; margin-bottom: 10px"
width="100%;" /> -->
<p class="content has-text-justified">
The emergence of Neural Radiance Fields (NeRF) has promoted the development of synthesized
high-fidelity views of the
intricate real world. However, it is still a very demanding task to repaint the content in
NeRF. In this paper, we
propose a novel framework that can take RGB images as input and alter the 3D content in
neural scenes. Our work
leverages existing diffusion models to guide changes in the designated 3D content.
Specifically, we semantically select
the object we want to modify first, and a pre-trained diffusion model will guide the NeRF
model to generate new 3D
objects, which can improve the editability, diversity, and application range of NeRF.
Experiment results show that our
algorithm is effective for editing 3D objects in NeRF under different text prompts,
including editing appearance, shape,
etc. We validate our method on real-world datasets and synthetic-world datasets for these
editing tasks. See
\url{https://repaintnerf.github.io} for a better view into our edited results.
</p>
</div>
</div>
</div>
<!--/ Abstract. -->
<!-- <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/WEgJf1WC5SQ" frameborder="0"
allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div>
</div>
</div> -->
</div>
</section>
<!-- 方法 -->
<section class="section">
<div class="container is-max-desktop">
<!-- Method. -->
<div class="columns is-centered has-text-centered">
<div class="column is-full">
<h2 class="title is-3">Edited Pipeline</h2>
<div class="content">
<img src="data/images/ov9.png" width="100%" />
</div>
</br>
<div class="content has-text-justified">
<p>
Overview of RePaint-NeRF. We present an editing method in NeRF. In the first stage, we
additionally optimize a feature
field along with the color module and density module
to extract the content mask by using text or patch. In another way of speaking, we separate
the part we want to change
for a generation. Then, we use the mask and text prompt to generate the new content guided
by the pre-trained diffusion
model and CLIP model. After optimization of the generation, we can finally repaint a
pre-trained NeRF model with view
consistency and
scene integrity.
</p>
</br>
</div>
</div>
</div>
<!--/ Method. -->
</div>
</section>
<!-- 视频 Qualitative Results-->
<section class="hero is-light is-small">
<div class="hero-body">
<div class="container has-text-centered">
<!-- <h2 class="title">Qualitative Results</h2> -->
<div id="results-carousel" class="carousel results-carousel">
<div class="item rounded-0 border-0 item-sink">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/man.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/man_i.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-sink">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/redcar.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/redcar_i.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-piano">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/flower.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/flower_i.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-light">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/hotdog.mp4" type="video/mp4">
</video>
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<source src="data/videos/hotdog_i.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-light">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/hotdog_i2.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/hotdog_i3.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-sink">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/chesstable.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/chesstable_i.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-light">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/fortress.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/fortress_i.mp4" type="video/mp4">
</video>
</div>
<div class="item rounded-0 border-0 item-light">
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/bench.mp4" type="video/mp4">
</video>
<video poster="" autoplay muted loop preload="none" class="w-auto" style="height:22vh;">
<source src="data/videos/bench_i.mp4" type="video/mp4">
</video>
</div>
</div>
</div>
</div>
</section>
<br />
<!-- BibTex -->
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@inproceedings{RePaint-NeRF,
title={{RePaint-NeRF}: NeRF Editting via Semantic Masks and Diffusion Models},
author={Zhou, Xingchen and He, Ying and Yu, F Richard and Li, Jianqiang and Li, You},
year={2023},
booktitle={IJCAI},
}</code></pre>
</div>
</section>
<!-- borrow -->
<footer class="footer">
<div class="container">
<div class="columns is-centered">
<div class="column is-8">
<div class="content">
<p>
Website template borrowed from <a
href="https://github.com/nerfies/nerfies.github.io">NeRFies</a> and <a
href="https://github.com/nesf3d/nesf3d.github.io">NeSF</a>.
</p>
</div>
</div>
</div>
</div>
</footer>
<p>
Website template borrowed from <a href="https://github.com/nerfies/nerfies.github.io">NeRFies</a> and <a
href="https://github.com/nesf3d/nesf3d.github.io">NeSF</a>.
</p>
</body>
</html>