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	<meta name="description" content="DoGaussian: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction Via Gaussian Consensus">

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	<h1 class="mt-3"><img src="assets/imgs/dog_icon.png" style="height: 50px; width: auto">DoGaussian: Distributed-Oriented Gaussian Splatting </h1>
	<h3 class="mb-4">for Large-Scale 3D Reconstruction Via Gaussian Consensus</h3>
	</div>
	<div class="row text-center">
	<div class="col-sm-0 col-md-2"></div>
	<div class="col-sm-12 col-md-8">
	<h6>
	<a href="https://aibluefisher.github.io/" target="_blank"><nobr>Yu Chen</nobr></a>
	<a href="https://www.comp.nus.edu.sg/~leegh/" target="_blank"><nobr>Gim Hee Lee</nobr></a>
	</h6>
	National University of Singapore
	</div>
	<div class="col-sm-0 col-md-2"></div>
	<div class="col-md-12 mt-3">
	<a href="https://arxiv.org/abs/2405.13943" class="btn btn-secondary btn-sm" target="_blank"><i class="fa-solid fa-file-pdf"></i>  arXiv</a>
	<a href="index.html" target="_blank" class="btn btn-secondary btn-sm"><i class="fa-brands fa-youtube"></i>  Video</a>
	<a href="https://github.com/aibluefisher/DoGaussian" target="_blank" class="btn btn-secondary btn-sm"><i class="fa-brands fa-github"></i>  Code</a>
	<a href="https://aibluefisher.github.io/dogaussian/#citation" class="btn btn-secondary btn-sm"><i class="fa-solid fa-file"></i>  BibTeX</a>
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	<video class="w-100 mt-4" autoplay="" loop="" muted="">
	<source src="assets/videos/DoGaussian_demo_final.mp4" type="video/mp4">
	</video>
	<!--
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	<h3 class="mt-3">Abstract</h3>
	<hr>
	<p>
	The recent advances in 3D Gaussian Splatting (3DGS) show promising results on the novel view
	synthesis (NVS) task. With its superior rendering performance and high-fidelity rendering quality,
	3DGS is excelling at its previous NeRF counterparts. The most recent 3DGS method focuses either on
	improving the instability of rendering efficiency or reducing the model size. On the other hand,
	the training efficiency of 3DGS on large-scale scenes has not gained much attention. In this work,
	we propose <b>DoGaussian</b>, a method that trains 3DGS distributedly. Our method first decomposes a scene into
	K blocks and then introduces the Alternating Direction Method of Multipliers (ADMM) into the training
	procedure of 3DGS. During training, our DoGaussian maintains one global 3DGS model on the master node and
	K local 3DGS models on the slave nodes. The K local 3DGS models are dropped after training and we only
	query the global 3DGS model during inference. The training time is reduced by scene decomposition,
	and the training convergence and stability are guaranteed through the consensus on the shared 3D Gaussians.
	Our method <b>accelerates the training of 3DGS by 6+ times</b> when evaluated on large-scale scenes while
	concurrently achieving state-of-the-art rendering quality.
	</p>


	<!-- <h3 class="mt-5" id="overview"> Watch a 3-minute overview video</h3>
	<hr class="hr">
	<video class="w-100 mb-4" controls="" preload="none" poster="assets/overview_video_poster.jpg">
	<source src="" type="video/mp4">
	</video> -->

	<h3 class="mt-5">Watch <b>DoGaussian</b> reconstructed large-scale scenes</h3>
	<hr class="hr">
	<p>
	We visualize the reconstruction results of <b>DoGaussian</b> on the Mill-19 and UrbanScene3D dataset.
	The results are recorded on <u>a browser of a MacBook (m1 chip with 8GB memory)</u> with freely moving
	camera trajectories that are highly different from the training views.
	<b>Use the controls to switch between scenes.</b>
	</p>

	<div id="DoGaussianResults" class="carousel slide" data-bs-ride="false">
	<div class="carousel-indicators">
	<button type="button" data-bs-target="#DoGaussianResults" data-bs-slide-to="0" class="active" aria-current="true" aria-label="Slide 1"></button>
	<button type="button" data-bs-target="#DoGaussianResults" data-bs-slide-to="1" aria-label="Slide 2"></button>
	<button type="button" data-bs-target="#DoGaussianResults" data-bs-slide-to="2" aria-label="Slide 3"></button>
	<button type="button" data-bs-target="#DoGaussianResults" data-bs-slide-to="3" aria-label="Slide 4"></button>
	<button type="button" data-bs-target="#DoGaussianResults" data-bs-slide-to="4" aria-label="Slide 5"></button>
	</div>
	<div class="carousel-inner">
	<div class="carousel-item active">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/building_dogaussian.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>Mill19 - Building</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/rubble_dogaussian.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>Mill-19 - Rubble</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/campus_dogaussian.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Campus</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/sciart_dogaussian.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Sci-Art</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/residence_dogaussian.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Residence</h5>
	</div>
	</div>
	</div>
	<button class="carousel-control-prev" type="button" data-bs-target="#DoGaussianResults" data-bs-slide="prev">
	<span class="carousel-control-prev-icon" aria-hidden="true"></span>
	<span class="visually-hidden">Previous</span>
	</button>
	<button class="carousel-control-next" type="button" data-bs-target="#DoGaussianResults" data-bs-slide="next">
	<span class="carousel-control-next-icon" aria-hidden="true"></span>
	<span class="visually-hidden">Next</span>
	</button>
	</div>

	<h3 class="mt-5">Watch <b>DoGaussian</b> reconstructed 3D Gaussian Primitives</h3>
	<hr class="hr">
	<p>
	We visualize the reconstructed 3D Gaussian primitives of <b>DoGaussian</b> on the Mill-19 and UrbanScene3D dataset.
	The results are recorded on <u>a browser of a MacBook (m1 chip with 8GB memory)</u> with freely moving
	camera trajectories that are highly different from the training views.
	<b>Use the controls to switch between scenes.</b>
	</p>

	<div id="DoGaussianPclResults" class="carousel slide" data-bs-ride="false">
	<div class="carousel-indicators">
	<button type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide-to="0" class="active" aria-current="true" aria-label="Slide 1"></button>
	<button type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide-to="1" aria-label="Slide 2"></button>
	<button type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide-to="2" aria-label="Slide 3"></button>
	<button type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide-to="3" aria-label="Slide 4"></button>
	<button type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide-to="4" aria-label="Slide 5"></button>
	</div>
	<div class="carousel-inner">
	<div class="carousel-item active">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/building_dogaussian_pcl.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>Mill19 - Building</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/rubble_dogaussian_pcl.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>Mill-19 - Rubble</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/campus_dogaussian_pcl.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Campus</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/sciart_dogaussian_pcl.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Sci-Art</h5>
	</div>
	</div>
	<div class="carousel-item">
	<video class="w-100" autoplay="" loop="" muted="">
	<source src="assets/videos/residence_dogaussian_pcl.mp4" type="video/mp4">
	</video>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Residence</h5>
	</div>
	</div>
	</div>
	<button class="carousel-control-prev" type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide="prev">
	<span class="carousel-control-prev-icon" aria-hidden="true"></span>
	<span class="visually-hidden">Previous</span>
	</button>
	<button class="carousel-control-next" type="button" data-bs-target="#DoGaussianPclResults" data-bs-slide="next">
	<span class="carousel-control-next-icon" aria-hidden="true"></span>
	<span class="visually-hidden">Next</span>
	</button>
	</div>

	<h3 class="mt-5">Training Pipeline of <b>DoGaussian</b></h3>
	<hr class="hr">

	<img class="w-100 mb-3" src="assets/imgs/dogaussian_pipeline.png" alt="">
	<p>
	(1) We first split the scene into K blocks with similar sizes. Each block is extended to a larger size
	to construct overlapping parts.
	<br>
	(2) Subsequently, we assign views and points into different blocks. The shared local 3D Gaussians
	(connected by solid lines in the figure) are a copy the the global 3D Gaussians.
	<br>
	(3) The local 3D Gaussians are then collected and averaged to the global 3D Gaussians in each consensus
	step, and the global 3D Gaussians are shared with each block before training all blocks.
	<br>
	(4) Finally, we use the final global 3D Gaussians to synthesize novel views.
	</p>

	<h3 class="mt-5"><b>DoGaussian</b> on novel view synthesis</h3>
	<hr class="hr">



	<!-- <div id="DoGaussianSliderResults" class="carousel slide" data-bs-ride="false">
	<div class="carousel-indicators">
	<button type="button" data-bs-target="#DoGaussianSliderResults" data-bs-slide-to="0" class="active" aria-current="true" aria-label="Slide 1"></button>
	<button type="button" data-bs-target="#DoGaussianSliderResults" data-bs-slide-to="1" aria-label="Slide 2"></button>
	<button type="button" data-bs-target="#DoGaussianSliderResults" data-bs-slide-to="2" aria-label="Slide 3"></button>
	<button type="button" data-bs-target="#DoGaussianSliderResults" data-bs-slide-to="3" aria-label="Slide 4"></button>
	</div>
	<div class="carousel-inner">
	<div class="carousel-item active">
	<div id="example6" class="bal-container-small">
	<div class="bal-after">
	<img class="d-block" src="./assets/imgs/campus_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="./assets/imgs/campus_mega-nerf.png">
	<div class="bal-beforePosition beforeLabel">
	Mega-NeRF [Turki, <i>et.al.</i> 2022]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class="handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Campus</h5>
	</div>
	</div>
	<div class="carousel-item">
	<div id="example7" class="bal-container-small">
	<div class="bal-after">
	<img src="./assets/imgs/building_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="./assets/imgs/building_switch-nerf.png">
	<div class="bal-beforePosition beforeLabel">
	Switch-NeRF [Mi & Xu 2023]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class="handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<div class="carousel-caption">
	<h5>Mill-19 - Building</h5>
	</div>
	</div>
	<div class="carousel-item">
	<div id="example8" class="bal-container-small">
	<div class="bal-after">
	<img src="./assets/imgs/rubble_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="./assets/imgs/rubble_3dgs.png">
	<div class="bal-beforePosition beforeLabel">
	3DGS [Kerbl, <i>et.al.</i> 2023]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class=" handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<div class="carousel-caption">
	<h5>Mill-19 - Rubble</h5>
	</div>
	</div>
	<div class="carousel-item">
	<div id="example9" class="bal-container-small">
	<div class="bal-after">
	<img src="./assets/imgs/sciart_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="./assets/imgs/sciart_vastgs.png">
	<div class="bal-beforePosition beforeLabel">
	VastGaussian [Lin, <i>et.al.</i> 2024]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class=" handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<div class="carousel-caption">
	<h5>UrbanScene3D - Sci-Art</h5>
	</div>
	</div>
	</div>
	<button class="carousel-control-prev" type="button" data-bs-target="#DoGaussianSliderResults" data-bs-slide="prev">
	<span class="carousel-control-prev-icon" aria-hidden="true"></span>
	<span class="visually-hidden">Previous</span>
	</button>
	<button class="carousel-control-next" type="button" data-bs-target="#DoGaussianSliderResults" data-bs-slide="next">
	<span class="carousel-control-next-icon" aria-hidden="true"></span>
	<span class="visually-hidden">Next</span>
	</button>
	</div> -->


	<div class="row align-items-start">
	<div id="example4" class="bal-container-small">
	<div class="bal-after">
	<img src="assets/imgs/campus_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="assets/imgs/campus_mega-nerf.png">
	<div class="bal-beforePosition beforeLabel">
	Mega-NeRF [Turki, <i>et.al.</i> 2022]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class=" handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<hr>

	<div id="example3" class="bal-container-small">
	<div class="bal-after">
	<img src="assets/imgs/building_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="assets/imgs/building_switch-nerf.png">
	<div class="bal-beforePosition beforeLabel">
	Switch-NeRF [Mi & Xu 2023]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class=" handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<hr>
	</div>

	<div class="row align-items-start">
	<div id="example1" class="bal-container-small">
	<div class="bal-after">
	<img src="assets/imgs/rubble_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="assets/imgs/rubble_3dgs.png">
	<div class="bal-beforePosition beforeLabel">
	3DGS [Kerbl, <i>et.al.</i> 2023]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class=" handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<hr>

	<div id="example2" class="bal-container-small">
	<div class="bal-after">
	<img src="assets/imgs/sciart_dogs.png">
	<div class="bal-afterPosition afterLabel" style="z-index:1;">
	Ours
	</div>
	</div>

	<div class="bal-before" style="width:6.369426751592357%;">
	<div class="bal-before-inset" style="width: 628px;">
	<img src="assets/imgs/sciart_vastgs.png">
	<div class="bal-beforePosition beforeLabel">
	VastGaussian [Lin, <i>et.al.</i> 2024]
	</div>
	</div>
	</div>

	<div class="bal-handle" style="left:6.369426751592357%;">
	<span class=" handle-left-arrow"></span>
	<span class="handle-right-arrow"></span>
	</div>
	</div>
	<hr>
	</div>

	<h3 class="mt-5" id="citation">Please consider citing our paper</h3>
	<hr class="hr">
	<pre class="w-100 user-select-all font-monospace border border-secondary bg-dark mb-5 p-2">@inproceedings{yuchen2024dogaussian,
	title={DoGaussian: Distributed-Oriented Gaussian Splatting for Large-Scale 3D Reconstruction Via Gaussian Consensus},
	author={Yu Chen, Gim Hee Lee},
	booktitle={arXiv},
	year={2024},
	}</pre>

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