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@toniwuest
toniwuest committed Jul 23, 2024
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190 changes: 20 additions & 170 deletions docs/index.html
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More Research
</a>
<div class="navbar-dropdown">
<!-- <a class="navbar-item" href="https://hypernerf.github.io">
HyperNeRF
</a>
<a class="navbar-item" href="https://nerfies.github.io">
Nerfies
</a>
<a class="navbar-item" href="https://latentfusion.github.io">
LatentFusion
</a>
<a class="navbar-item" href="https://photoshape.github.io">
PhotoShape
</a> -->
<a class="navbar-item" href="https://ml-research.github.io/NeuralConceptBinder/" target="_blank">
Neural Concept Binder
</a>
</div>
</div>
</div>
Expand All @@ -78,19 +69,22 @@ <h1 class="title is-1 publication-title">Pix2Code: Learning to Compose Neural Vi
</h1>
<div class="is-size-5 publication-authors">
<span class="author-block">
<a href="https://ml-research.github.io/people/awuest/index.html">Antonia
<a href="https://ml-research.github.io/people/awuest/index.html" target="_blank">Antonia
W&uuml;st</a><sup>1</sup>,</span>
<span class="author-block">
<a href="https://ml-research.github.io/people/wstammer/index.html">Wolfgang
<a href="https://ml-research.github.io/people/wstammer/index.html" target="_blank">Wolfgang
Stammer</a><sup>1,2</sup>,</span>
<span class="author-block">
<a href="https://ml-research.github.io/people/qdelfosse/index.html">Quentin Delfosse</a><sup>1</sup>,
<a href="https://ml-research.github.io/people/qdelfosse/index.html" target="_blank">Quentin
Delfosse</a><sup>1</sup>,
</span>
<span class="author-block">
<a href="https://sites.google.com/view/devendradhami">Devendra Singh Dhami</a><sup>3</sup>,
<a href="https://sites.google.com/view/devendradhami" target="_blank">Devendra Singh
Dhami</a><sup>3</sup>,
</span>
<span class="author-block">
<a href="https://homes.cs.washington.edu/~seitz/">Kristian Kersting</a><sup>1,2,4,5</sup>,
<a href="https://ml-research.github.io/people/kkersting/" target="_blank">Kristian
Kersting</a><sup>1,2,4,5</sup>,
</span>
</div>

Expand All @@ -106,35 +100,28 @@ <h1 class="title is-1 publication-title">Pix2Code: Learning to Compose Neural Vi
<div class="publication-links">
<!-- PDF Link. -->
<span class="link-block">
<a href="https://arxiv.org/pdf/2402.08280" class="external-link button is-normal is-rounded is-dark">
<a href="https://arxiv.org/pdf/2402.08280" class="external-link button is-normal is-rounded is-dark"
target="_blank">
<span class="icon">
<i class="fas fa-file-pdf"></i>
</span>
<span>Paper</span>
</a>
</span>
<span class="link-block">
<a href="https://arxiv.org/abs/2402.08280" class="external-link button is-normal is-rounded is-dark">
<a href="https://arxiv.org/abs/2402.08280" class="external-link button is-normal is-rounded is-dark"
target="_blank">
<span class="icon">
<i class="ai ai-arxiv"></i>
</span>
<span>arXiv</span>
</a>
</span>
<!-- Video Link. -->
<!-- <span class="link-block">
<a href="https://www.youtube.com/watch?v=MrKrnHhk8IA"
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/ml-research/pix2code"
class="external-link button is-normal is-rounded is-dark">
class="external-link button is-normal is-rounded is-dark" target="_blank">
<span class="icon">
<i class="fab fa-github"></i>
</span>
Expand All @@ -144,7 +131,7 @@ <h1 class="title is-1 publication-title">Pix2Code: Learning to Compose Neural Vi
<!-- Dataset Link. -->
<span class="link-block">
<a href="https://hessenbox.tu-darmstadt.de/getlink/fi4qz3W54u3cPs1AdS5AHxK7/rel_kp.zip"
class="external-link button is-normal is-rounded is-dark">
class="external-link button is-normal is-rounded is-dark" target="_blank">
<span class="icon">
<i class="far fa-images"></i>
</span>
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</div>
</section>

<!--
<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-steve">
<video poster="" id="steve" autoplay controls muted loop playsinline height="100%">
<source src="./static/videos/steve.mp4" type="video/mp4">
</video>
</div>
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<source src="./static/videos/chair-tp.mp4" type="video/mp4">
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<source src="./static/videos/shiba.mp4" type="video/mp4">
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<source src="./static/videos/fullbody.mp4" type="video/mp4">
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<source src="./static/videos/mask.mp4" type="video/mp4">
</video>
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<video poster="" id="coffee" autoplay controls muted loop playsinline height="100%">
<source src="./static/videos/coffee.mp4" type="video/mp4">
</video>
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<div class="item item-toby">
<video poster="" id="toby" autoplay controls muted loop playsinline height="100%">
<source src="./static/videos/toby2.mp4" type="video/mp4">
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</div>
</div>
</div>
</section> -->


<section class="hero is-light is-small">
<div class="hero-body">
<div class="container is-max-desktop">
Expand All @@ -243,8 +179,8 @@ <h2 class="title is-3">Abstract</h2>
To tackle both the generalizability and interpretability constraints of visual concept learning,
we propose Pix2Code, a framework that extends
program synthesis to visual relational reasoning
by utilizing the abilities of both explicit, compositional symbolic and implicit neural representa-
tions. This is achieved by retrieving object representations from images and synthesizing relational
by utilizing the abilities of both explicit, compositional symbolic and implicit neural representations.
This is achieved by retrieving object representations from images and synthesizing relational
concepts as λ-calculus programs.
We evaluate the diverse properties of Pix2Code on the challenging
reasoning domains, Kandinsky Patterns, and CURI,
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</div>
<!--/ Abstract. -->

<!-- Paper video. -->
<!-- <div class="columns is-centered has-text-centered">
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<h2 class="title is-3">Video</h2>
<div class="publication-video">
<iframe src="https://www.youtube.com/embed/MrKrnHhk8IA?rel=0&amp;showinfo=0" frameborder="0"
allow="autoplay; encrypted-media" allowfullscreen></iframe>
</div>
</div>
</div> -->
<!--/ Paper video. -->
</div>
</div>
</section>
Expand All @@ -278,45 +203,6 @@ <h2 class="title is-3">Video</h2>
<section class="section">
<div class="container is-max-desktop">

<!-- <div class="columns is-centered"> -->

<!-- Visual Effects. -->
<!-- <div class="column">
<div class="content">
<h2 class="title is-3">Visual Effects</h2>
<p>
Using <i>nerfies</i> you can create fun visual effects. This Dolly zoom effect
would be impossible without nerfies since it would require going through a wall.
</p>
<video id="dollyzoom" autoplay controls muted loop playsinline height="100%">
<source src="./static/videos/dollyzoom-stacked.mp4" type="video/mp4">
</video>
</div>
</div> -->
<!--/ Visual Effects. -->

<!-- Matting. -->
<!-- <div class="column">
<h2 class="title is-3">Matting</h2>
<div class="columns is-centered">
<div class="column content">
<p>
As a byproduct of our method, we can also solve the matting problem by ignoring
samples that fall outside of a bounding box during rendering.
</p>
<video id="matting-video" controls playsinline height="100%">
<source src="./static/videos/matting.mp4" type="video/mp4">
</video>
</div>
</div>
</div>
</div> -->
<!--/ Matting. -->

<!-- Method overview -->
<!--/ Method overview -->

<!-- Interpretability. -->
<div class="columns is-centered">
<div class="column is-full-width">
Expand Down Expand Up @@ -405,42 +291,6 @@ <h3 class="title is-3">Human revision of <span class="method">Pix2Code</span></h
</div>
<!--/ Human revision. -->



<!-- Concurrent Work. -->
<!-- <div class="columns is-centered">
<div class="column is-full-width">
<h2 class="title is-3">Related Links</h2>
<div class="content has-text-justified">
<p>
There's a lot of excellent work that was introduced around the same time as ours.
</p>
<p>
<a href="https://arxiv.org/abs/2104.09125">Progressive Encoding for Neural Optimization</a> introduces an
idea similar to our windowed position encoding for coarse-to-fine optimization.
</p>
<p>
<a href="https://www.albertpumarola.com/research/D-NeRF/index.html">D-NeRF</a> and <a
href="https://gvv.mpi-inf.mpg.de/projects/nonrigid_nerf/">NR-NeRF</a>
both use deformation fields to model non-rigid scenes.
</p>
<p>
Some works model videos with a NeRF by directly modulating the density, such as <a
href="https://video-nerf.github.io/">Video-NeRF</a>, <a
href="https://www.cs.cornell.edu/~zl548/NSFF/">NSFF</a>, and <a
href="https://neural-3d-video.github.io/">DyNeRF</a>
</p>
<p>
There are probably many more by the time you are reading this. Check out <a
href="https://dellaert.github.io/NeRF/">Frank Dellart's survey on recent NeRF papers</a>, and <a
href="https://github.com/yenchenlin/awesome-NeRF">Yen-Chen Lin's curated list of NeRF papers</a>.
</p>
</div>
</div>
</div> -->
<!--/ Concurrent Work. -->

</div>
</section>

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/*color: hsl(204, 86%, 53%) !important;*/
color: #0cc8cc;
color: #0dc4e1;
color: #e08b4a;
}

.publication-authors a:hover {
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