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<!DOCTYPE html>
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<head>
<meta charset="utf-8">
<meta name="description"
content="Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos.">
<meta name="keywords" content="Nerfies, D-NeRF, NeRF">
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<title>NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions</title>
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<h1 class="title is-1 publication-title">NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://scholar.google.com.hk/citations?user=qbovRUIAAAAJ">Juze Zhang</a><sup>1,2,3,4</sup>*,</span>
<span class="author-block">
<a href="https://haiminluo.github.io/">Haimin Luo</a><sup>1,4</sup>*,</span>
<span class="author-block">
<a>Hongdi Yang</a><sup>1,4</sup>,
</span>
<span class="author-block">
<a>Xinru Xu</a><sup>1,4</sup>,
</span>
<span class="author-block">
<a>Qianyang Wu</a><sup>1,4</sup>,
</span>
<span class="author-block">
<a href="https://shiye21.github.io/">Ye Shi</a><sup>1,4</sup>,
</span>
<span class="author-block">
<a href="http://www.yu-jingyi.com/cv/">Jingyi Yu</a><sup>1,4</sup>
</span>
<span class="author-block">
<a href="https://www.xu-lan.com/">Lan Xu</a><sup>1,4</sup>†
</span>
<span class="author-block">
<a href="https://faculty.sist.shanghaitech.edu.cn/faculty/wangjingya/">Jingya Wang</a><sup>1,4</sup>†
</span>
</div>
<div class="is-size-5 publication-authors">
<span class="author-block"><sup>1</sup>ShanghaiTech University,</span>
<span class="author-block"><sup>2</sup>Shanghai Advanced Research Institute, Chinese Academy of Sciences</span>
<span class="author-block"><sup>3</sup>University of Chinese Academy of Sciences</span>
<span class="author-block"><sup>4</sup>Shanghai Engineering Research Center of Intelligent Vision and Imaging</span>
<span class="author-block"><sup>*</sup>These authors contributed equally.</span>
<span class="author-block"><sup>†</sup>Corresponding author</span>
</div>
<div class="column has-text-centered">
<div class="publication-links">
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<a href="https://openaccess.thecvf.com/content/CVPR2023/papers/Zhang_NeuralDome_A_Neural_Modeling_Pipeline_on_Multi-View_Human-Object_Interactions_CVPR_2023_paper.pdf"
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<span>arXiv</span>
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<span>Data</span>
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</section>
<section class="hero teaser">
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<p><img src="NeuralDome.png" alt="" style="max-width:100%;"></p>
<h2 class="subtitle has-text-centered">
</h2>
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<h2 class="title is-3">Abstract</h2>
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<p>
Humans constantly interact with objects in daily life
tasks. Capturing such processes and subsequently conducting visual inferences from a fixed viewpoint suffers from
occlusions, shape and texture ambiguities, motions, etc.
To mitigate the problem, it is essential to build a training
dataset that captures free-viewpoint interactions. We construct a dense multi-view dome to acquire a complex human object interaction dataset, named HODome, that consists of ∼71M frames on 10 subjects interacting with 23
objects. To process the HODome dataset, we develop NeuralDome, a layer-wise neural processing pipeline tailored
for multi-view video inputs to conduct accurate tracking,
geometry reconstruction and free-view rendering, for both
human subjects and objects. Extensive experiments on the
HODome dataset demonstrate the effectiveness of NeuralDome on a variety of inference, modeling, and rendering
tasks. Both the dataset and the NeuralDome tools will be
disseminated to the community for further development.
</p>
</div>
</div>
</div>
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<h2 class="title is-3">Video</h2>
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frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
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<!--/ Paper video. -->
</div>
</section>
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@inproceedings{
zhang2023neuraldome,
title={NeuralDome: A Neural Modeling Pipeline on Multi-View Human-Object Interactions},
author={Juze Zhang and Haimin Luo and Hongdi Yang and Xinru Xu and Qianyang Wu and Ye Shi and Jingyi Yu and Lan Xu and Jingya Wang},
booktitle={CVPR},
year={2023},
}</code></pre>
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