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index.html
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<html>
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<head>
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<meta charset="utf-8">
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<meta name="description"
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<meta name="keywords" content="Nerfies, D-NeRF, NeRF">
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<meta name="viewport" content="width=device-width, initial-scale=1">
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<title>
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<link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro"
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rel="stylesheet">
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<link rel="stylesheet" href="./static/css/bulma.min.css">
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<link rel="stylesheet" href="./static/css/bulma-carousel.min.css">
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<link rel="stylesheet" href="./static/css/bulma-slider.min.css">
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<link rel="stylesheet" href="./static/css/fontawesome.all.min.css">
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<link rel="stylesheet"
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href="https://cdn.jsdelivr.net/gh/jpswalsh/academicons@1/css/academicons.min.css">
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<link rel="stylesheet" href="./static/css/index.css">
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<link rel="icon" href="./static/images/favicon.svg">
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<div class="container is-max-desktop">
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<div class="columns is-centered">
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<div class="column has-text-centered">
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<h1 class="title is-1 publication-title">
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<div class="is-size-5 publication-authors">
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<span class="author-block">
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<a href="https://keunhong.com" target="_blank">Keunhong Park</a><sup>1</sup>,</span>
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<span class="author-block">
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<a href="https://utkarshsinha.com" target="_blank">Utkarsh Sinha</a><sup>2</sup>,</span>
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<span class="author-block">
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<a href="https://jonbarron.info" target="_blank">Jonathan T. Barron</a><sup>2</sup>,
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</span>
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<span class="author-block">
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<a href="http://sofienbouaziz.com" target="_blank">Sofien Bouaziz</a><sup>2</sup>,
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</span>
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<span class="author-block">
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<a href="https://www.danbgoldman.com" target="_blank">Dan B Goldman</a><sup>2</sup>,
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</span>
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<span class="author-block">
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<a href="https://homes.cs.washington.edu/~seitz/" target="_blank">Steven M. Seitz</a><sup>1,2</sup>,
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</span>
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<span class="author-block">
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<a href="http://www.ricardomartinbrualla.com" target="_blank">Ricardo Martin-Brualla</a><sup>2</sup>
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</span>
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</div>
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<div class="is-size-5 publication-authors">
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<span class="author-block"
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<span class="author-block"><sup>2</sup>Google Research</span>
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</div>
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<div class="column has-text-centered">
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<div class="publication-links">
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<!-- PDF Link. -->
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<span class="link-block">
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<a href="https://
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<span
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<i class="fas fa-file-pdf"></i>
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</span>
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<span>Paper</span>
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</a>
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</span>
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<span class="link-block">
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<a href="https://
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<span
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<i class="ai ai-arxiv"></i>
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</span>
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<span>arXiv</span>
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</a>
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</span>
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<!-- Video Link. -->
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<span class="link-block">
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<a href="https://
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<span
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<i class="fab fa-youtube"></i>
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</span>
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<span>Video</span>
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</a>
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</span>
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<!-- Code Link. -->
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<span class="link-block">
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<a href="https://github.com/google/nerfies" target="_blank"
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class="external-link button is-normal is-rounded is-dark">
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<span class="icon">
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<i class="fab fa-github"></i>
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</span>
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<span>Code</span>
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</a>
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</span>
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<!-- Dataset Link. -->
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<span class="link-block">
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<a href="https://github.com/google/nerfies/releases/tag/0.1" target="_blank"
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class="external-link button is-normal is-rounded is-dark">
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<span class="icon">
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<i class="far fa-images"></i>
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</span>
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<span>Data</span>
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</a>
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<section class="hero teaser">
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<div class="container is-max-desktop">
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<div class="hero-body">
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<video id="teaser" autoplay muted loop playsinline height="100%">
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<source src="./static/videos/teaser.mp4"
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type="video/mp4">
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</video>
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<h2 class="subtitle has-text-centered">
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<span class="dnerf">
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free-viewpoint
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portraits.
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</h2>
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<video poster="" id="steve" autoplay controls muted loop playsinline height="100%">
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<source src="./static/videos/steve.mp4"
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type="video/mp4">
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</video>
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<div class="item item-chair-tp">
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<video poster="" id="chair-tp" autoplay controls muted loop playsinline height="100%">
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<source src="./static/videos/chair-tp.mp4"
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type="video/mp4">
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</video>
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<div class="item item-shiba">
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<video poster="" id="shiba" autoplay controls muted loop playsinline height="100%">
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<source src="./static/videos/shiba.mp4"
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type="video/mp4">
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</video>
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</div>
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<div class="item item-fullbody">
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<video poster="" id="fullbody" autoplay controls muted loop playsinline height="100%">
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<source src="./static/videos/fullbody.mp4"
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type="video/mp4">
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<video poster="" id="blueshirt" autoplay controls muted loop playsinline height="100%">
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</video>
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<video poster="" id="mask" autoplay controls muted loop playsinline height="100%">
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</video>
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<video poster="" id="coffee" autoplay controls muted loop playsinline height="100%">
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type="video/mp4">
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</video>
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<video poster="" id="toby" autoplay controls muted loop playsinline height="100%">
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<source src="./static/videos/toby2.mp4"
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type="video/mp4">
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</video>
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</section>
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<section class="section">
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<div class="container is-max-desktop">
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<!-- Abstract. -->
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<div class="columns is-centered has-text-centered">
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<div class="column is-four-fifths">
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<h2 class="title is-3">
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<div class="content has-text-justified">
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<p>
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deforming scene using photos/videos captured casually from mobile phones.
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</p>
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<p>
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Our approach augments neural radiance fields
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(NeRF) by optimizing an
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additional continuous volumetric deformation field that warps each observed point into a
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canonical 5D NeRF.
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We observe that these NeRF-like deformation fields are prone to local minima, and
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propose a coarse-to-fine optimization method for coordinate-based models that allows for
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more robust optimization.
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By adapting principles from geometry processing and physical simulation to NeRF-like
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models, we propose an elastic regularization of the deformation field that further
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improves robustness.
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</p>
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<p>
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We show that <span class="dnerf">Nerfies</span> can turn casually captured selfie
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photos/videos into deformable NeRF
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models that allow for photorealistic renderings of the subject from arbitrary
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viewpoints, which we dub <i>"nerfies"</i>. We evaluate our method by collecting data
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using a
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rig with two mobile phones that take time-synchronized photos, yielding train/validation
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images of the same pose at different viewpoints. We show that our method faithfully
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reconstructs non-rigidly deforming scenes and reproduces unseen views with high
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fidelity.
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</p>
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<!--/ Abstract. -->
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<div class="columns is-centered has-text-centered">
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<h2 class="title is-3">Video</h2>
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<div class="publication-video">
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<iframe src="https://www.youtube.com/embed/MrKrnHhk8IA?rel=0&showinfo=0"
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frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
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<!--/ Paper video. -->
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</section>
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<section class="section">
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<div class="container is-max-desktop">
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<div class="columns is-centered">
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<!-- Visual Effects. -->
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<div class="column">
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<div class="content">
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samples that fall outside of a bounding box during rendering.
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</p>
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<video id="matting-video" controls playsinline height="100%">
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<source src="./static/videos/matting.mp4"
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type="video/mp4">
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</video>
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<div class="columns is-centered">
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<div class="column is-
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<h2 class="title is-3">Animation</h2>
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<!-- Interpolating. -->
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<h3 class="title is-4">Interpolating states</h3>
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<div class="content has-text-justified">
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<p>
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We can also animate the scene by interpolating the deformation latent codes of two input
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frames. Use the slider here to linearly interpolate between the left frame and the right
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frame.
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</p>
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</div>
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<div class="columns is-vcentered interpolation-panel">
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<div class="column is-3 has-text-centered">
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<img src="./static/images/interpolate_start.jpg"
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class="interpolation-image"
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alt="Interpolate start reference image."/>
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<p>Start Frame</p>
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</div>
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<div class="column interpolation-video-column">
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<input class="slider is-fullwidth is-large is-info"
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id="interpolation-slider"
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step="1" min="0" max="100" value="0" type="range">
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</div>
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<div class="column is-3 has-text-centered">
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<img src="./static/images/interpolate_end.jpg"
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class="interpolation-image"
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alt="Interpolation end reference image."/>
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<p class="is-bold">End Frame</p>
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</div>
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</div>
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<br/>
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<h3 class="title is-4">Re-rendering the input video</h3>
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<div class="content has-text-justified">
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<video id="replay-video"
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controls
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<!--/ Concurrent Work. -->
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</div>
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</section>
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<section class="section" id="BibTeX">
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<div class="container is-max-desktop content">
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<h2 class="title">BibTeX</h2>
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<pre><code>@
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}</code></pre>
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</div>
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</section>
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<footer class="footer">
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<div class="container">
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<div class="content has-text-centered">
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<a class="icon-link" target="_blank"
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href="./static/videos/nerfies_paper.pdf">
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<h1 class="title is-1 publication-title">LangGraph Agent Chat UI</h1>
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<span class="author-block">A React/Vite Interface for LangGraph Agents</span>
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Your Gateway to Seamless Agent Interaction with <span class="dnerf">LangGraph</span>
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The <strong>Agent Chat UI</strong> is a React/Vite application that provides a clean, chat-based interface for interacting with your LangGraph agents. It’s designed to work seamlessly with LangGraph’s core features, including checkpoints, thread management, and human-in-the-loop capabilities.
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<p>Here’s why it’s a valuable tool:</p>
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<ul>
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<li><strong>Easy Connection:</strong> Connect to local or deployed LangGraph agents with a simple URL and graph ID.</li>
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<li><strong>Intuitive Chat:</strong> Interact naturally with your agents in a familiar chat format.</li>
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<li><strong>Visualize Agent Actions:</strong> See tool calls and their results rendered directly in the UI.</li>
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<li><strong>Human-in-the-Loop Made Easy:</strong> Seamlessly integrate human input using LangGraph’s <code>interrupt</code> feature.</li>
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<li><strong>Explore Execution Paths:</strong> Travel through time, inspect checkpoints, and fork conversations.</li>
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<li><strong>Debug and Understand:</strong> Inspect the full state of your LangGraph thread at any point.</li>
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</ul>
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<section class="section">
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<h2 class="title is-3 has-text-centered">Get Started</h2>
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<div class="content">
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<h3 class="title is-4">1. Try the Deployed Version (No Setup Required!)</h3>
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<ul>
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<li><strong>Visit:</strong> <a href="https://agentchat.vercel.app/" target="_blank">agentchat.vercel.app</a></li>
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<li><strong>Connect:</strong> Enter your LangGraph deployment URL and graph ID (the <code>path</code> set with <code>langserve.add_routes</code>). For production, include your LangSmith API key.</li>
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<li><strong>Chat!</strong> Start interacting with your agent.</li>
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</ul>
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<h3 class="title is-4">2. Run Locally (Development & Customization)</h3>
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<p><strong>Option A: Clone the Repository</strong></p>
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<pre><code>git clone https://github.com/langchain-ai/agent-chat-ui.git
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cd agent-chat-ui
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pnpm install # Or npm install/yarn install
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pnpm dev # Or npm run dev/yarn dev</code></pre>
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<p><strong>Option B: Quickstart with <code>npx</code></strong></p>
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<pre><code>npx create-agent-chat-app
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cd agent-chat-app
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pnpm install # Or npm install/yarn install
|
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pnpm dev # Or npm run dev/yarn dev</code></pre>
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<p>Open your browser to <code>http://localhost:5173</code>.</p>
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</div>
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</section>
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<section class="section">
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<div class="container is-max-desktop">
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<h2 class="title is-3 has-text-centered">Features</h2>
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<div class="columns is-centered">
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<div class="content has-text-justified">
|
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+
<ul>
|
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<li><strong>Easy Connection:</strong> Connect to local or production LangGraph deployments with a URL and graph ID.</li>
|
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+
<li><strong>Chat Interface:</strong> Real-time messaging with automatic checkpoint persistence.</li>
|
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<li><strong>Tool Call Rendering:</strong> Visualize tool calls and results, compatible with LangGraph’s <a href="https://python.langchain.com/docs/guides/tools/custom_tools" target="_blank">tool calling</a>.</li>
|
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+
<li><strong>Human-in-the-Loop Support:</strong> Review, edit, and respond to interrupts using LangGraph’s <code>interrupt</code> function.</li>
|
| 141 |
+
<li><strong>Thread History:</strong> Navigate past interactions with checkpointing.</li>
|
| 142 |
+
<li><strong>Time Travel and Forking:</strong> Explore execution paths with LangGraph’s <a href="https://python.langchain.com/docs/modules/agents/concepts#checkpointing" target="_blank">checkpointing</a>.</li>
|
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+
<li><strong>State Inspection:</strong> Debug by examining the full LangGraph thread state.</li>
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</ul>
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</div>
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</div>
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</section>
|
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+
<section class="section">
|
| 152 |
+
<div class="container is-max-desktop">
|
| 153 |
+
<h2 class="title is-3 has-text-centered">LangGraph Setup Examples</h2>
|
| 154 |
<div class="columns is-centered">
|
| 155 |
+
<div class="column is-four-fifths">
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<div class="content">
|
| 157 |
+
<h3 class="title is-4">Basic LangGraph Agent</h3>
|
| 158 |
+
<pre><code class="language-python"># agent.py
|
| 159 |
+
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
|
| 160 |
+
from langchain_openai import ChatOpenAI
|
| 161 |
+
from langgraph.prebuilt import create_agent_executor
|
| 162 |
+
from langserve import add_routes
|
| 163 |
+
from fastapi import FastAPI
|
| 164 |
+
|
| 165 |
+
prompt = ChatPromptTemplate.from_messages([
|
| 166 |
+
("system", "You are a helpful assistant"),
|
| 167 |
+
MessagesPlaceholder(variable_name="messages"),
|
| 168 |
+
MessagesPlaceholder(variable_name="agent_scratchpad"),
|
| 169 |
+
])
|
| 170 |
+
model = ChatOpenAI(temperature=0)
|
| 171 |
+
agent = {"messages": lambda x: x["messages"], "agent_scratchpad": lambda x: []} | prompt | model
|
| 172 |
+
app = create_agent_executor(agent, [])
|
| 173 |
+
fastapi_app = FastAPI(title="LangGraph Agent")
|
| 174 |
+
add_routes(fastapi_app, app, path="/chat")
|
| 175 |
+
|
| 176 |
+
if __name__ == "__main__":
|
| 177 |
+
import uvicorn
|
| 178 |
+
uvicorn.run(fastapi_app, host="localhost", port=2024)
|
| 179 |
+
</code></pre>
|
| 180 |
+
<p>Run at <code>http://localhost:2024/chat</code> with graph ID <code>chat</code>.</p>
|
| 181 |
+
|
| 182 |
+
<h3 class="title is-4">Human-in-the-Loop Example</h3>
|
| 183 |
+
<pre><code class="language-python"># agent.py
|
| 184 |
+
from langgraph.prebuilt import create_agent_executor, interrupt
|
| 185 |
+
from langchain_core.tools import tool
|
| 186 |
+
|
| 187 |
+
@tool
|
| 188 |
+
def write_email(subject: str, body: str, to: str):
|
| 189 |
+
return f"Draft email to {to} with subject {subject} sent."
|
| 190 |
+
|
| 191 |
+
tools = [write_email]
|
| 192 |
+
model = ChatOpenAI(model="gpt-4-turbo-preview").bind_tools(tools)
|
| 193 |
+
|
| 194 |
+
def handle_interrupt(state):
|
| 195 |
+
messages = state["messages"]
|
| 196 |
+
if isinstance(messages[-1].content, list):
|
| 197 |
+
for msg in messages[-1].content:
|
| 198 |
+
if isinstance(msg, ToolInvocation) and msg.name == "write_email":
|
| 199 |
+
return interrupt(messages, {"type": "interrupt", "args": {"type": "response", "studio": msg.args}})
|
| 200 |
+
return {"messages": messages}
|
| 201 |
+
|
| 202 |
+
agent = {"messages": lambda x: x["messages"], "agent_scratchpad": lambda x: []} | prompt | model | handle_interrupt
|
| 203 |
+
app = create_agent_executor(agent, tools)
|
| 204 |
+
fastapi_app = FastAPI(title="LangGraph Agent")
|
| 205 |
+
add_routes(fastapi_app, app, path="/email_agent")
|
| 206 |
+
|
| 207 |
+
if __name__ == "__main__":
|
| 208 |
+
import uvicorn
|
| 209 |
+
uvicorn.run(fastapi_app, host="localhost", port=2024)
|
| 210 |
+
</code></pre>
|
| 211 |
+
<p>Run at <code>http://localhost:2024/email_agent</code> with graph ID <code>email_agent</code>.</p>
|
| 212 |
</div>
|
| 213 |
</div>
|
| 214 |
</div>
|
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| 215 |
</div>
|
| 216 |
</section>
|
| 217 |
|
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|
| 218 |
<section class="section" id="BibTeX">
|
| 219 |
<div class="container is-max-desktop content">
|
| 220 |
<h2 class="title">BibTeX</h2>
|
| 221 |
+
<pre><code>@misc{langgraph2023agentchat,
|
| 222 |
+
title = {LangGraph Agent Chat UI},
|
| 223 |
+
author = {LangChain Team},
|
| 224 |
+
year = {2023},
|
| 225 |
+
url = {https://github.com/langchain-ai/agent-chat-ui}
|
| 226 |
}</code></pre>
|
| 227 |
</div>
|
| 228 |
</section>
|
| 229 |
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| 230 |
<footer class="footer">
|
| 231 |
<div class="container">
|
| 232 |
<div class="content has-text-centered">
|
| 233 |
+
<a class="icon-link" href="https://github.com/langchain-ai/agent-chat-ui" target="_blank">
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| 234 |
<i class="fab fa-github"></i>
|
| 235 |
</a>
|
| 236 |
</div>
|
|
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| 238 |
<div class="column is-8">
|
| 239 |
<div class="content">
|
| 240 |
<p>
|
| 241 |
+
This website is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/" target="_blank">Creative Commons Attribution-ShareAlike 4.0 International License</a>.
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