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https://liuff19.github.io/ReconX/

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16    content="ReconX, unleashes the strong generative prior of video diffusion model for sparse-view 3D scene reconstruction. ">
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19  <title>ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model
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63            <h1 class="title is-1 publication-title"><span
64                style="color: #48a7b5  ;font-weight: bolder;">ReconX</span>: Reconstruct Any Scene from Sparse Views with Video Diffusion Model</h1>
65            <div class="is-size-5 publication-authors">
66              <span class="author-block">  
67                <a href="https://liuff19.github.io/">Fangfu Liu</a><sup>1</sup><sup>*</sup>,</span>
68              <span class="author-block">
69                <a href="https://github.com/wenqsun">Wenqiang Sun</a><sup>2</sup><sup>*</sup>,</span>
70              <span class="author-block">
71                <a href="https://hanyang-21.github.io/">Hanyang Wang</a><sup>1</sup><sup>*</sup>,</span>
72              <span class="author-block">
73                <a href="https://yikaiw.github.io/">Yikai Wang</a><sup>1</sup>,</span>
74              <span class="author-block">
75                <a href="https://github.com/sunboy0617">Haowen Sun</a><sup>1</sup>,</span><br>
76              <span class="author-block">
77                <a href="https://jamesyjl.github.io/">Junliang Ye</a><sup>1</sup>,</span>
78              <span class="author-block">
79                <a href="https://eejzhang.people.ust.hk/home.html">Jun Zhang</a><sup>2</sup>,</span>
80              <span class="author-block">
81                <a href="https://duanyueqi.github.io/">Yueqi Duan</a><sup>1</sup></span>
82          </div>
83
84          <!-- affiliations -->
85          <div class="subtitle is-size-5">
86          <!-- <div class="is-size-5 publication-authors"> -->
87            <sup>1</sup> Tsinghua University &nbsp;
88            <sup>2</sup> HKUST <br>
89            <sup>*</sup> Equal Contribution
90            <!-- <span class="author-block"><sup>1</sup>The University of Texas at Austin</span>
91            <span class="author-block"><sup>2</sup>Nvidia</span> <br>
92            <span class="author-block"><sup>3</sup>Xiamen University</span> <br>
93            <span class="author-block"><sup>4</sup>Georgia Institute of Technology</span> <br>
94            <span class="author-block"><sup>5</sup>Stanford University</span> <br>
95            <span class="author-block"><sup>6</sup>University of Southern California</span> <br>
96            <span class="author-block"><sup>*</sup>denotes equal contribution</span> -->
97          </div>
98
99          <!-- TODO: update paper and video link once upload -->
100          <div class="column has-text-centered">
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104              <a href="https://arxiv.org/pdf/2408.16767"
105                 class="external-link button is-normal is-rounded is-dark">
106                <span class="icon">
107                    <i class="fas fa-file-pdf"></i>
108                </span>
109                <span>Paper</span>
110              </a>
111              </span>
112              <span class="link-block">
113              <a href="https://arxiv.org/abs/2408.16767"
114                 class="external-link button is-normal is-rounded is-dark">
115                <span class="icon">
116                    <i class="ai ai-arxiv"></i>
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118                <span>arXiv</span>
119              </a>
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127                  <span>Video</span>
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132                <a href="https://github.com/liuff19/ReconX"
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137                  <span>Code</span>
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142                <a href="https://github.com/liuff19/ReconX"
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176  </section>
177
178<hr>
179<section class="hero teaser">
180  <div class="container is-max-desktop">
181    <div class="hero-body">
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184          <h2 class="title is-3">Video</h2>
185          <div class="publication-video">
186            <iframe src="https://www.youtube.com/embed/UuL2nP5rJcI?rel=0&showinfo=0"
187                    frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
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191      <!-- <video id="teaser" autoplay controls loop playsinline height="100%"> -->
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193      <!-- </video> -->
194      <h2 class="subtitle has-text-justified">
195        <b>ReconX</b> is a novel sparse-view 3D scene reconstruction paradigm that reframes the ambiguous reconstruction challenge as a temporal generation task.
196      </h2>
197    </div>
198  </div>
199</section>
200  
201
202
203  <section class="section">
204    <div class="container is-max-desktop">
205      <!-- Abstract. -->
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208          <h2 class="title is-3">Abstract</h2>
209          <div class="content has-text-justified">
210            <img src="./static/images/teaser.png">
211            <p>
212              Advancements in 3D scene reconstruction have transformed 2D images from the real world into 3D models, producing realistic 3D results from hundreds of input photos. Despite great success in dense-view reconstruction scenarios, rendering a detailed scene from insufficient captured views is still an ill-posed optimization problem, often resulting in artifacts and distortions in unseen areas. In this paper, we propose <strong>ReconX</strong>, a novel 3D scene reconstruction paradigm that reframes the ambiguous reconstruction challenge as a temporal generation task. The key insight is to unleash the strong generative prior of large pre-trained video diffusion models for sparse-view reconstruction. However, 3D view consistency struggles to be accurately preserved in directly generated video frames from pre-trained models. To address this, given limited input views, the proposed ReconX first constructs a global point cloud and encodes it into a contextual space as the 3D structure condition. Guided by the condition, the video diffusion model then synthesizes video frames that are both detail-preserved and exhibit a high degree of 3D consistency, ensuring the coherence of the scene from various perspectives. Finally, we recover the 3D scene from the generated video through a confidence-aware 3D Gaussian Splatting optimization scheme. Extensive experiments on various real-world datasets show the superiority of our ReconX over state-of-the-art methods in terms of quality and generalizability.
213            </p>
214          </div>
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219    </div>
220  </section>
221
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225      <!-- Concurrent Work. -->
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228          <h2 class="title is-3">Method Overview</h2>
229          <div class="content has-text-justified">
230            <img src="./static/images/method.png">
231
232            <p><strong>Overall Framework of ReconX</strong>. Given sparse-view images as input, we first build a global point cloud
233              and project it into 3D context representation space as 3D structure guidance. Then we inject the 3D
234              structure guidance into the video diffusion process and guide it to generate 3D consistent video
235              frames. Finally, we reconstruct the 3D scene from the generated video through Gaussian Splatting
236              with a 3D confidence-aware and robust scene optimization scheme. In this way, we unleash the
237              strong power of the video diffusion model to reconstruct intricate 3D scenes from very sparse views.</p>
238
239          </div>
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244    </div>
245  </section>
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247  <section class="section">
248    <div class="container is-max-desktop">
249      <div class="columns is-centered has-text-centered">
250        <div class="column is-full-width">
251          <h2 class="title is-3">Real-World Results of ReconX</h2>
252          <div class="content has-text-justified">
253      </div>
254    </div>
255  </section>
256  <section class="hero is-light is-small">
257    <div class="hero-body">
258      <div class="container">
259        <div id="results-carousel" class=" carousel results-carousel">        
260          <div class="item item-family">
261            <video poster="" id="family" autoplay controls muted loop playsinline height="100%">
262              <source src="./static/videos/museum.mp4"
263                      type="video/mp4">
264            </video>
265          </div>   
266          <div class="item item-family">
267            <video poster="" id="family" autoplay controls muted loop playsinline height="100%">
268              <source src="./static/videos/airport.mp4"
269                      type="video/mp4">
270            </video>
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273            <video poster="" id="horse" autoplay controls muted loop playsinline height="100%">
274              <source src="./static/videos/bighouse.mp4"
275                      type="video/mp4">
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277          </div>
278          <div class="item item-horse">
279            <video poster="" id="horse" autoplay controls muted loop playsinline height="100%">
280              <source src="./static/videos/playroom.mp4"
281                      type="video/mp4">
282            </video>
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284          <div class="item item-horse">
285            <video poster="" id="horse" autoplay controls muted loop playsinline height="100%">
286              <source src="./static/videos/khouse.mp4"
287                      type="video/mp4">
288            </video>
289          </div>
290        </div>
291        <p>The results shown are derived from <strong>two or three sparse views as input</strong>.</p>
292      </div>
293    </div>
294  </section>
295
296  <section class="section">
297    <div class="container is-max-desktop ">
298      <div class=" has-text-centered">
299        <h2 class="title is-3">Visual Comparisons</h2>
300        <div class="content has-text-justified">
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316                        ReconX [Ours]
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322                        <img src="./static/images/comparison_n/scene1/pixelsplat.png">
323                        <div class="bal-beforePosition beforeLabel">
324                          pixelSplat [Charatan 2024]
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340                        ReconX [Ours]
341                      </div>
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345                      <div class="bal-before-inset" style="width: 512px;">
346                        <img src="./static/images/comparison_n/scene1/mvsplat.png">
347                        <div class="bal-beforePosition beforeLabel">
348                          MVSplat [Chen 2023]
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376                  <div class="bal-after">
377                    <img src="./static/images/comparison_n/scene-gen/reconx.png">
378                    <div class="bal-afterPosition afterLabel">
379                      ReconX [Ours]
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383                  <div class="bal-before" style="width: 50%;">
384                    <div class="bal-before-inset" style="width: 512px;">
385                      <img src="./static/images/comparison_n/scene-gen/pixelsplat.png">
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387                        pixelSplat [Charatan 2024]
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403                      ReconX [Ours]
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408                    <div class="bal-before-inset" style="width: 512px;">
409                      <img src="./static/images/comparison_n/scene-gen/mvsplat.png">
410                      <div class="bal-beforePosition beforeLabel">
411                        MVSplat [Chen 2023]
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435                    <img src="./static/images/comparison_n/scene3/reconx.png">
436                    <div class="bal-afterPosition afterLabel">
437                      ReconX [Ours]
438                    </div>
439                  </div>
440
441                  <div class="bal-before" style="width: 50%;">
442                    <div class="bal-before-inset" style="width: 512px;">
443                      <img src="./static/images/comparison_n/scene3/pixelsplat.png">
444                      <div class="bal-beforePosition beforeLabel">
445                        pixelSplat [Charatan 2024]
446                      </div>
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457                  <div class="bal-after">
458                    <img src="./static/images/comparison_n/scene3/reconx.png">
459                    <div class="bal-afterPosition afterLabel" style="z-index:1;">
460                      ReconX [Ours]
461                    </div>
462                  </div>
463
464                  <div class="bal-before" style="width:56.77179962894249%;">
465                    <div class="bal-before-inset" style="width: 512px;">
466                      <img src="./static/images/comparison_n/scene3/mvsplat.png">
467                      <div class="bal-beforePosition beforeLabel">
468                        MVSplat [Chen 2023]
469                      </div>
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519        <h2 class="title is-3">Related Links</h2>
520
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522          <p>
523            Needs update
524          </p>
525         
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530  </div>
531</section> -->
532
533
534  <section class="section" id="BibTeX">
535    <div class="container is-max-desktop content">
536      <h2 class="title">BibTeX</h2>
537      <pre><code>@misc{liu2024reconxreconstructscenesparse,
538        title={ReconX: Reconstruct Any Scene from Sparse Views with Video Diffusion Model}, 
539        author={Fangfu Liu and Wenqiang Sun and Hanyang Wang and Yikai Wang and Haowen Sun and Junliang Ye and Jun Zhang and Yueqi Duan},
540        year={2024},
541        eprint={2408.16767},
542        archivePrefix={arXiv},
543        primaryClass={cs.CV},
544        url={https://arxiv.org/abs/2408.16767},
545      }</code></pre>
546    </div>
547  </section>
548  
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