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@@ -3,10 +3,10 @@
 <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">
   <meta name="viewport" content="width=device-width, initial-scale=1">
-  <title>Nerfies: Deformable Neural Radiance Fields</title>
   <link href="https://fonts.googleapis.com/css?family=Google+Sans|Noto+Sans|Castoro"
         rel="stylesheet">
@@ -33,86 +33,24 @@
     <div class="container is-max-desktop">
       <div class="columns is-centered">
         <div class="column has-text-centered">
-          <h1 class="title is-1 publication-title">Nerfies: Deformable Neural Radiance Fields</h1>
           <div class="is-size-5 publication-authors">
-            <span class="author-block">
-              <a href="https://keunhong.com" target="_blank">Keunhong Park</a><sup>1</sup>,</span>
-            <span class="author-block">
-              <a href="https://utkarshsinha.com" target="_blank">Utkarsh Sinha</a><sup>2</sup>,</span>
-            <span class="author-block">
-              <a href="https://jonbarron.info" target="_blank">Jonathan T. Barron</a><sup>2</sup>,
-            </span>
-            <span class="author-block">
-              <a href="http://sofienbouaziz.com" target="_blank">Sofien Bouaziz</a><sup>2</sup>,
-            </span>
-            <span class="author-block">
-              <a href="https://www.danbgoldman.com" target="_blank">Dan B Goldman</a><sup>2</sup>,
-            </span>
-            <span class="author-block">
-              <a href="https://homes.cs.washington.edu/~seitz/" target="_blank">Steven M. Seitz</a><sup>1,2</sup>,
-            </span>
-            <span class="author-block">
-              <a href="http://www.ricardomartinbrualla.com" target="_blank">Ricardo Martin-Brualla</a><sup>2</sup>
-            </span>
-          </div>
-          <div class="is-size-5 publication-authors">
-            <span class="author-block"><sup>1</sup>University of Washington,</span>
-            <span class="author-block"><sup>2</sup>Google Research</span>
           </div>
           <div class="column has-text-centered">
             <div class="publication-links">
-              <!-- PDF Link. -->
-              <span class="link-block">
-                <a href="https://arxiv.org/pdf/2011.12948" target="_blank"
-                   class="external-link button is-normal is-rounded is-dark">
-                  <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/2011.12948" target="_blank"
-                   class="external-link button is-normal is-rounded is-dark">
-                  <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" target="_blank"
                    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/google/nerfies" target="_blank"
-                   class="external-link button is-normal is-rounded is-dark">
-                  <span class="icon">
-                      <i class="fab fa-github"></i>
-                  </span>
-                  <span>Code</span>
-                  </a>
-              </span>
-              <!-- Dataset Link. -->
-              <span class="link-block">
-                <a href="https://github.com/google/nerfies/releases/tag/0.1" target="_blank"
-                   class="external-link button is-normal is-rounded is-dark">
-                  <span class="icon">
-                      <i class="far fa-images"></i>
-                  </span>
-                  <span>Data</span>
-                  </a>
             </div>
           </div>
         </div>
       </div>
@@ -120,311 +58,111 @@
   </div>
 </section>
-<section class="hero teaser">
   <div class="container is-max-desktop">
-    <div class="hero-body">
-      <video id="teaser" autoplay muted loop playsinline height="100%">
-        <source src="./static/videos/teaser.mp4"
-                type="video/mp4">
-      </video>
-      <h2 class="subtitle has-text-centered">
-        <span class="dnerf">Nerfies</span> turns selfie videos from your phone into
-        free-viewpoint
-        portraits.
-      </h2>
-    </div>
-  </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>
-        <div class="item item-chair-tp">
-          <video poster="" id="chair-tp" autoplay controls muted loop playsinline height="100%">
-            <source src="./static/videos/chair-tp.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <div class="item item-shiba">
-          <video poster="" id="shiba" autoplay controls muted loop playsinline height="100%">
-            <source src="./static/videos/shiba.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <div class="item item-fullbody">
-          <video poster="" id="fullbody" autoplay controls muted loop playsinline height="100%">
-            <source src="./static/videos/fullbody.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <div class="item item-blueshirt">
-          <video poster="" id="blueshirt" autoplay controls muted loop playsinline height="100%">
-            <source src="./static/videos/blueshirt.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <div class="item item-mask">
-          <video poster="" id="mask" autoplay controls muted loop playsinline height="100%">
-            <source src="./static/videos/mask.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <div class="item item-coffee">
-          <video poster="" id="coffee" autoplay controls muted loop playsinline height="100%">
-            <source src="./static/videos/coffee.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <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">
-          </video>
         </div>
       </div>
     </div>
-  </div>
-</section>
-<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 present the first method capable of photorealistically reconstructing a non-rigidly
-            deforming scene using photos/videos captured casually from mobile phones.
           </p>
           <p>
-            Our approach augments neural radiance fields
-            (NeRF) by optimizing an
-            additional continuous volumetric deformation field that warps each observed point into a
-            canonical 5D NeRF.
-            We observe that these NeRF-like deformation fields are prone to local minima, and
-            propose a coarse-to-fine optimization method for coordinate-based models that allows for
-            more robust optimization.
-            By adapting principles from geometry processing and physical simulation to NeRF-like
-            models, we propose an elastic regularization of the deformation field that further
-            improves robustness.
           </p>
           <p>
-            We show that <span class="dnerf">Nerfies</span> can turn casually captured selfie
-            photos/videos into deformable NeRF
-            models that allow for photorealistic renderings of the subject from arbitrary
-            viewpoints, which we dub <i>"nerfies"</i>. We evaluate our method by collecting data
-            using a
-            rig with two mobile phones that take time-synchronized photos, yielding train/validation
-            images of the same pose at different viewpoints. We show that our method faithfully
-            reconstructs non-rigidly deforming scenes and reproduces unseen views with high
-            fidelity.
           </p>
-        </div>
-      </div>
-    </div>
-    <!--/ Abstract. -->
-    <!-- Paper video. -->
-    <div class="columns is-centered has-text-centered">
-      <div class="column is-four-fifths">
-        <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>
-</section>
-<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. -->
-    <!-- Animation. -->
-    <div class="columns is-centered">
-      <div class="column is-full-width">
-        <h2 class="title is-3">Animation</h2>
-        <!-- Interpolating. -->
-        <h3 class="title is-4">Interpolating states</h3>
-        <div class="content has-text-justified">
           <p>
-            We can also animate the scene by interpolating the deformation latent codes of two input
-            frames. Use the slider here to linearly interpolate between the left frame and the right
-            frame.
           </p>
-        </div>
-        <div class="columns is-vcentered interpolation-panel">
-          <div class="column is-3 has-text-centered">
-            <img src="./static/images/interpolate_start.jpg"
-                 class="interpolation-image"
-                 alt="Interpolate start reference image."/>
-            <p>Start Frame</p>
-          </div>
-          <div class="column interpolation-video-column">
-            <div id="interpolation-image-wrapper">
-              Loading...
-            </div>
-            <input class="slider is-fullwidth is-large is-info"
-                   id="interpolation-slider"
-                   step="1" min="0" max="100" value="0" type="range">
-          </div>
-          <div class="column is-3 has-text-centered">
-            <img src="./static/images/interpolate_end.jpg"
-                 class="interpolation-image"
-                 alt="Interpolation end reference image."/>
-            <p class="is-bold">End Frame</p>
-          </div>
-        </div>
-        <br/>
-        <!--/ Interpolating. -->
-        <!-- Re-rendering. -->
-        <h3 class="title is-4">Re-rendering the input video</h3>
-        <div class="content has-text-justified">
           <p>
-            Using <span class="dnerf">Nerfies</span>, you can re-render a video from a novel
-            viewpoint such as a stabilized camera by playing back the training deformations.
           </p>
         </div>
-        <div class="content has-text-centered">
-          <video id="replay-video"
-                 controls
-                 muted
-                 preload
-                 playsinline
-                 width="75%">
-            <source src="./static/videos/replay.mp4"
-                    type="video/mp4">
-          </video>
-        </div>
-        <!--/ Re-rendering. -->
       </div>
     </div>
-    <!--/ Animation. -->
-    <!-- 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" target="_blank">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" target="_blank">D-NeRF</a> and <a href="https://gvv.mpi-inf.mpg.de/projects/nonrigid_nerf/" target="_blank">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/" target="_blank">Video-NeRF</a>, <a href="https://www.cs.cornell.edu/~zl548/NSFF/" target="_blank">NSFF</a>, and <a href="https://neural-3d-video.github.io/" target="_blank">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/" target="_blank">Frank Dellart's survey on recent NeRF papers</a>, and <a href="https://github.com/yenchenlin/awesome-NeRF" target="_blank">Yen-Chen Lin's curated list of NeRF papers</a>.
           </p>
         </div>
       </div>
     </div>
-    <!--/ Concurrent Work. -->
-  </div>
-</section>
-<section class="section" id="BibTeX">
-  <div class="container is-max-desktop content">
-    <h2 class="title">BibTeX</h2>
-    <pre><code>@article{park2021nerfies,
-  author    = {Park, Keunhong and Sinha, Utkarsh and Barron, Jonathan T. and Bouaziz, Sofien and Goldman, Dan B and Seitz, Steven M. and Martin-Brualla, Ricardo},
-  title     = {Nerfies: Deformable Neural Radiance Fields},
-  journal   = {ICCV},
-  year      = {2021},
-}</code></pre>
   </div>
 </section>
 <footer class="footer">
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-      <a class="icon-link" target="_blank"
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-        <i class="fas fa-file-pdf"></i>
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-          <p>
-            This means you are free to borrow the <a target="_blank"
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@@ -432,4 +170,4 @@
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+        content="Réflexion IA - Questions and answers about artificial intelligence.">
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+        <div class="content has-text-justified">
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+            Welcome to Réflexion IA, a space dedicated to exploring the complexities of artificial intelligence through questions and answers.
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+        <h2 class="title is-3">Frequently Asked Questions</h2>
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+          <p><strong>What is artificial intelligence?</strong></p>
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+            Artificial intelligence (AI) refers to systems or machines that mimic human intelligence to perform tasks and can iteratively improve themselves based on the information they collect. AI manifests in various forms, from chatbots to autonomous vehicles and smart assistants.
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+          <p><strong>How does machine learning differ from AI?</strong></p>
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+            Machine learning is a subset of AI that focuses on the development of algorithms that enable computers to learn from and make decisions based on data. While AI is the broader concept of machines being able to carry out tasks in a way that we would consider "smart," machine learning is a specific application of AI based around the idea that machines should be able to learn and adapt through experience.
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+          <p><strong>What are neural networks?</strong></p>
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+            Neural networks are computing systems with interconnected nodes that work similarly to neurons in the human brain. These systems "learn" to perform tasks by analyzing examples, generally without being programmed with task-specific rules. They are particularly good at identifying patterns and can be trained to recognize images, translate languages, and make predictions.
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+          <p><strong>What ethical concerns surround AI development?</strong></p>
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+          <p><strong>How will AI impact the job market?</strong></p>
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+            AI is likely to automate certain tasks and potentially eliminate some jobs, particularly those involving routine or predictable activities. However, it is also expected to create new job categories and transform existing ones. The key challenge will be helping workers transition to new roles and ensuring that the benefits of AI-driven productivity are broadly shared.
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+        <h2 class="title is-3">Further Reading</h2>
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           <p>
+            For more information on artificial intelligence and related topics, consider exploring these resources:
           </p>
           <p>
+            <a href="#" target="_blank">Understanding Machine Learning Fundamentals</a>
           </p>
           <p>
+            <a href="#" target="_blank">Ethical AI: Principles and Practices</a>
           </p>
           <p>
+            <a href="#" target="_blank">The History and Future of Artificial Intelligence</a>
           </p>
           <p>
+            <a href="#" target="_blank">AI in Everyday Life: Applications and Implications</a>
           </p>
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       </div>
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+    <!--/ Additional Info -->
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