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<!DOCTYPE html>
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<meta name="description" content="DGD is a method to distill 2D semantic features to dynamic 3D Gaussian Splatting scenes, allowing for semantic segmentation of dynamic objects in 3D.">
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<title>DGD: Dynamic 3D Gaussians Distillation</title>
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<section class="hero">
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<div class="container is-max-desktop">
<div class="columns is-centered">
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<h1 class="title is-1 publication-title">DGD: Dynamic 3D Gaussians Distillation</h1>
<!-- Add ECCV 2024 with larger size -->
<div class="is-size-3 has-text-weight-bold">ECCV 2024</div>
<!-- Paper Authors -->
<div class="is-size-5 publication-authors">
<span class="author-block">
<a>Isaac Labe</a><sup>1</sup>
</span>
<span class="author-block">
<a>Noam Issachar</a><sup>1</sup>
</span>
<span class="author-block">
<a href="https://itailang.github.io">Itai Lang</a><sup>2</sup>
</span>
<span class="author-block">
<a href="https://sagiebenaim.github.io">Sagie Benaim</a><sup>1</sup>
</span>
</div>
<!-- End of Paper Authors -->
<!-- Institutions -->
<div class="is-size-5 publication-authors">
<span class="author-block">
<sup>1</sup>The Hebrew University of Jerusalem <sup>2</sup>University of Chicago
</span>
</div>
<!-- End of Institutions -->
<!-- Publication Links -->
<div class="column has-text-centered">
<div class="publication-links">
<!-- Paper link -->
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<a href="https://arxiv.org/pdf/2405.19321" target="_blank"
class="external-link button is-normal is-rounded is-dark">
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<span>Paper</span>
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<a href="https://arxiv.org/abs/2405.19321" target="_blank"
class="external-link button is-normal is-rounded is-dark">
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<span>arXiv</span>
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<a href="https://github.com/Isaaclabe/DGD-Dynamic-3D-Gaussians-Distillation"
class="external-link button is-normal is-rounded is-dark">
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<span>Code</span>
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</div>
</div>
</section>
<!-- Results carousel -->
<section class="hero is-light is-small">
<div class="hero-body">
<div class="container">
<div id="results-carousel" class="carousel results-carousel">
<div class="item item-lamp-positive">
<video poster="" id="lamp-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/video_seg_cookie_dino.mp4" type="video/mp4">
</video>
<p class="has-text-centered">red: "Hands", green: "Cookie"</p>
</div>
<div class="item item-bike-positive">
<video poster="" id="bike-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/video_seg_coffee.mp4" type="video/mp4">
</video>
<p class="has-text-centered">red: "Hand", green: "Cup"</p>
</div>
<div class="item item-alien-positive">
<video poster="" id="alien-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/video_seg_chicken.mp4" type="video/mp4">
</video>
<p class="has-text-centered">red: "Hands", green: "Chicken"</p>
</div>
<div class="item item-camel-positive">
<video poster="" id="camel-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/video_seg_torch.mp4" type="video/mp4">
</video>
<p class="has-text-centered">red: "Hands"/"arms", green: "Torch"</p>
</div>
<div class="item item-hammer-positive-negative">
<video poster="" id="hammer-positive-negative" autoplay muted loop playsinline height="100%">
<source src="./static/videos/video_seg_cookie_clip_text.mp4" type="video/mp4">
</video>
<p class="has-text-centered">CLIP segmentation: "hands"-"cookie"</p>
</div>
</div>
</div>
</div>
</section>
<!-- End of results carousel -->
<!-- Teaser video -->
<section class="hero teaser">
<div class="container is-max-desktop">
<div class="hero-body">
<h2 class="subtitle has-text-centered">
<br>
<b>TL;DR:</b> We distill 2D semantic features to dynamic 3D Gaussian Splatting scenes, allowing for semantic segmentation of dynamic objects in 3D.
</h2>
</div>
</div>
</section>
<!-- End of teaser video -->
<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>
We tackle the task of learning dynamic 3D semantic radiance
fields given a single monocular video as input. Our learned semantic radiance
field captures per-point semantics as well as color and geometric
properties for a dynamic 3D scene, enabling the generation of novel views
and their corresponding semantics. This enables the segmentation and
tracking of a diverse set of 3D semantic entities, specified using a simple
and intuitive interface that includes a user click or a text prompt. To this
end, we present DGD, a unified 3D representation for both the appearance
and semantics of a dynamic 3D scene, building upon the recently
proposed dynamic 3D Gaussians representation. Our representation is
optimized over time with both color and semantic information. Key to
our method is the joint optimization of the appearance and semantic
attributes, which jointly affect the geometric properties of the scene. We
evaluate our approach in its ability to enable dense semantic 3D object
tracking and demonstrate high-quality results that are fast to render, for
a diverse set of scenes.
</p>
</div>
</div>
</div>
<!--/ end of Abstract -->
<!-- Video section -->
<div class="section">
<h2 class="title is-3 has-text-centered">Video</h2>
<div class="has-text-centered">
<video controls width="80%" muted>
<source src="./static/videos/Video_ECCV_DGD.mp4" type="video/mp4">
Your browser does not support the video tag.
</video>
</div>
</div>
</div>
</section>
<section class="section">
<div class="container is-max-desktop">
<!-- Method Overview-->
<div class="columns is-centered">
<div class="column is-full-width">
<hr class="divider" />
<h2 class="title is-3">Method Overview</h2>
<div class="content has-text-justified">
<p>
Dynamic 3D Gaussians Distillation utilizes 3D Gaussian representation and optimizes
spatial parameters of the Gaussians and their deformation, concurrently with
appearance properties with a semantic feature per Gaussian. Our learned representation
enables efficient semantic understanding and manipulation of dynamic 3D scenes.
</p>
</div>
<div class="two-col-image">
<img src="./static/images/system.png" type="image/png">
</div>
</div>
</div>
<!-- End of Method Overview-->
<!-- Results -->
<div class="columns is-centered">
<div class="column is-full-width">
<hr class="divider" />
<h2 class="title is-3">Results</h2>
<div class="content has-text-justified">
<p>
The following results show a fixed novel view over different timesteps using our method for semantically segmenting objects over time in the real-world HyperNerf dataset. The considered objects are marked in green and red.
<table width="200" border="0" align="center">
<tbody>
<tr>
<td align="center">
<video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_cookie.mp4" type="video/mp4" />
</video>
</td>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_torch.mp4" type="video/mp4" />
</video></td>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_chicken.mp4" type="video/mp4" />
</video></td>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_coffee.mp4" type="video/mp4" />
</video></td>
</tr>
<tr>
<td align="center">Cookie (green), Hands (red)</td>
<td align="center">Torch (green), Hands (red)</td>
<td align="center">Chicken (green), Hands (red)</td>
<td align="center">Cup (green), Hands (red)</td>
</tr>
</tr>
</tbody>
</table>
<p>
The following result are for the synthetic D-NeRF dataset. The considered parts are marked by green, yellow, and red colors.
<table width="200" border="0" align="center">
<tbody>
<tr>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_Trex.mp4" type="video/mp4" />
</video></td>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_standup.mp4" type="video/mp4" />
</video></td>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_jack.mp4" type="video/mp4" />
</video></td>
<td align="center"><video width="200" autoplay muted playsinline loop>
<source src="./static/videos/Single_novel_view/video_hook.mp4" type="video/mp4" />
</video></td>
</tr>
<tr>
<td align="center" width=250>red: "Spine", yellow: "Ribs", green: "Skull"</td>
<td align="center" width=250>red: "Face", yellow: "Shoes", green: "Helmet"</td>
<td align="center" width=250>red: "Pants", yellow: "Hair", green: "Hands"</td>
<td align="center" width=250>yellow: "Feets", green: "Hands"</td>
</tr>
<!-- </tr>-->
</tbody>
</table>
</p>
</div>
</div>
</div>
<!-- End of Results -->
<!-- Segmentation with differents foundation models -->
<div class="columns is-centered">
<div class="column is-full-width">
<hr class="divider" />
<h2 class="title is-3">Segmentation with different foundation models</h2>
<div class="content has-text-justified">
<p>
Our method leverages various 2D foundation models, including DINOv2, Lseg (CLIP), a combination of DINOv2 and Lseg and SAM, to effectively capture and understand the semantics of 3D scenes.
</p>
</div>
</div>
</div>
<!-- End of Segmentation with differents foundation models -->
<!-- Results carousel -->
<section class="hero is-light is-small">
<div class="hero-body">
<div class="container">
<div id="results-carousel" class="carousel results-carousel">
<div class="item item-lamp-positive">
<video poster="" id="lamp-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Backbones/video_seg_cookie_dino.mp4" type="video/mp4">
</video>
<p class="has-text-centered">DINOv2 (click)</p>
</div>
<div class="item item-bike-positive">
<video poster="" id="bike-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Backbones/video_seg_cookie_clip_text.mp4" type="video/mp4">
</video>
<p class="has-text-centered">Lseg (text prompt)</p>
</div>
<div class="item item-alien-positive">
<video poster="" id="alien-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Backbones/video_seg_cookie_clip_click_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">Lseg (click)</p>
</div>
<div class="item item-camel-positive">
<video poster="" id="camel-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Backbones/video_seg_cookie_clipdino_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">DINOv2 and Lseg (click)</p>
</div>
<div class="item item-hammer-positive-negative">
<video poster="" id="hammer-positive-negative" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Backbones/video_seg_cookie_sam_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">SAM (click)</p>
</div>
</div>
</div>
</div>
</section>
<!-- End of results carousel -->
<!-- Granularity -->
<div class="columns is-centered">
<div class="column is-full-width">
<hr class="divider" />
<h2 class="title is-3">Granularity</h2>
<div class="content has-text-justified">
<p>
Our semantic understanding of the scene captures fine-grained details, allowing us to control the click segmentation's granularity by adjusting the parameter θ.
</p>
</div>
</div>
</div>
<!-- End of Granularity -->
<!-- Results carousel -->
<section class="hero is-light is-small">
<div class="hero-body">
<div class="container">
<div id="results-carousel" class="carousel results-carousel">
<div class="item item-lamp-positive">
<video poster="" id="lamp-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Granularity/video_090_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">θ = 0.9</p>
</div>
<div class="item item-bike-positive">
<video poster="" id="bike-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Granularity/video_085_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">θ = 0.85</p>
</div>
<div class="item item-alien-positive">
<video poster="" id="alien-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Granularity/video_080_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">θ = 0.8</p>
</div>
<div class="item item-camel-positive">
<video poster="" id="camel-positive" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Granularity/video_075_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">θ = 0.75</p>
</div>
<div class="item item-hammer-positive-negative">
<video poster="" id="hammer-positive-negative" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Granularity/video_070_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">θ = 0.7</p>
</div>
<div class="item item-hammer-positive-negative">
<video poster="" id="hammer-positive-negative" autoplay muted loop playsinline height="100%">
<source src="./static/videos/Granularity/video_060_sloww.mp4" type="video/mp4">
</video>
<p class="has-text-centered">θ = 0.6</p>
</div>
</div>
</div>
</div>
</section>
<!-- End of results carousel -->
<!-- Results -->
<div class="columns is-centered">
<div class="column is-full-width">
<hr class="divider" />
<h2 class="title is-3">Editing</h2>
<div class="content has-text-justified">
Visual illustration of our method’s ability to semantically edit segmented and
tracked objects. Given the segmented region of the “cookie” (resp. “torch”), we consider
the ability to edit its texture using the prompt “strawberry” (resp. “handgun”). Here,
we display a randomly selected novel view over time. </p>
<table width="200" border="0" align="center">
<tbody>
<tr>
<td align="center">A red strawberry</td>
<td></td>
<td align="center">A black handgun</td>
</tr>
<tr>
<td align="center"><video width="200" controls="controls" autoplay muted playsinline loop>
<source src="./static/videos/editing/strawberry.mp4" type="video/mp4" />
</video></td>
<td align="center"><video width="10">
<td align="center"><video width="200" controls="controls" autoplay muted playsinline loop>
<source src="./static/videos/editing/handgun.mp4" type="video/mp4" />
</video></td>
</tr>
</tr>
</tbody>
</table>
<!--BibTex -->
<section class="section" id="BibTeX">
<div class="container is-max-desktop content">
<h2 class="title">BibTeX</h2>
<pre><code>@misc{labe2024dgd,
title={DGD: Dynamic 3D Gaussians Distillation},
author={Isaac Labe and Noam Issachar and Itai Lang and Sagie Benaim},
year={2024},
eprint={2405.19321},
archivePrefix={arXiv},
primaryClass={cs.CV}
}</code></pre>
</div>
</section>
<!-- End of BibTex -->
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