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@@ -2679,6 +2679,35 @@ <h2 class="paper-title">Advancing Extended Reality with 3D Gaussian Splatting: I
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+<div class="paper-row" data-id="javed2024temporally" data-title="Temporally Compressed 3D Gaussian Splatting for Dynamic Scenes" data-authors="Saqib Javed, Ahmad Jarrar Khan, Corentin Dumery, Chen Zhao, Mathieu Salzmann" data-year="2024" data-tags='["Acceleration", "Code", "Compression", "Dynamic", "Object Detection", "Optimization", "Project", "Rendering", "Robotics", "Video"]'>
+  <div class="paper-card">
+    <input type="checkbox" class="selection-checkbox" onclick="handleCheckboxClick(event, 'javed2024temporally', this)">
+    <div class="paper-number"></div>
+    <div class="paper-thumbnail">
+      <img data-src="assets/thumbnails/javed2024temporally.jpg" data-fallback="None" alt="Paper thumbnail for Temporally Compressed 3D Gaussian Splatting for Dynamic Scenes" class="lazy" loading="lazy"/>
+    </div>
+    <div class="paper-content">
+      <h2 class="paper-title">Temporally Compressed 3D Gaussian Splatting for Dynamic Scenes <span class="paper-year">(2024)</span></h2>
+      <p class="paper-authors">Saqib Javed, Ahmad Jarrar Khan, Corentin Dumery, Chen Zhao, Mathieu Salzmann</p>
+      <div class="paper-tags"><span class="paper-tag">Acceleration</span>
+<span class="paper-tag">Code</span>
+<span class="paper-tag">Compression</span>
+<span class="paper-tag">Dynamic</span>
+<span class="paper-tag">Object Detection</span>
+<span class="paper-tag">Optimization</span>
+<span class="paper-tag">Project</span>
+<span class="paper-tag">Rendering</span>
+<span class="paper-tag">Robotics</span>
+<span class="paper-tag">Video</span></div>
+      <div class="paper-links"><a href="https://arxiv.org/pdf/2412.05700.pdf" class="paper-link" target="_blank" rel="noopener">📄 Paper</a>
+<a href="https://ahmad-jarrar.github.io/tc-3dgs/" class="paper-link" target="_blank" rel="noopener">🌐 Project</a>
+<a href="https://github.com/saqibjaved1/TC3DGS" class="paper-link" target="_blank" rel="noopener">💻 Code</a>
+<button class="abstract-toggle" onclick="toggleAbstract(this)">📖 Show Abstract</button>
+<div class="paper-abstract">Recent advancements in high-fidelity dynamic scene reconstruction have leveraged dynamic 3D Gaussians and 4D Gaussian Splatting for realistic scene representation. However, to make these methods viable for real-time applications such as AR/VR, gaming, and rendering on low-power devices, substantial reductions in memory usage and improvements in rendering efficiency are required. While many state-of-the-art methods prioritize lightweight implementations, they struggle in handling scenes with complex motions or long sequences. In this work, we introduce Temporally Compressed 3D Gaussian Splatting (TC3DGS), a novel technique designed specifically to effectively compress dynamic 3D Gaussian representations. TC3DGS selectively prunes Gaussians based on their temporal relevance and employs gradient-aware mixed-precision quantization to dynamically compress Gaussian parameters. It additionally relies on a variation of the Ramer-Douglas-Peucker algorithm in a post-processing step to further reduce storage by interpolating Gaussian trajectories across frames. Our experiments across multiple datasets demonstrate that TC3DGS achieves up to 67$\times$ compression with minimal or no degradation in visual quality.
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+    </div>
+  </div>
+</div>
 <div class="paper-row" data-id="fan2024momentumgs" data-title="Momentum-GS: Momentum Gaussian Self-Distillation for High-Quality Large Scene Reconstruction" data-authors="Jixuan Fan, Wanhua Li, Yifei Han, Yansong Tang" data-year="2024" data-tags='["Code", "Large-Scale", "Project", "Video"]'>
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