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rename "densification" methods to "compaction" methods to align with…
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… survey paper
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paulbzm committed Oct 21, 2024
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2 changes: 2 additions & 0 deletions README.md
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Expand Up @@ -119,6 +119,8 @@ If you use our survey in your research, please cite our work. You can use the fo

## Updates

- 2024-10-21: Officialy rename "densification" methods to "compaction" methods on website to align with survey paper
- 2024-10-17: Add GaussiansPro, AtomGS and Taming3DGS to densification/compaction methods
- 2024-10-14: Add MesonGS to compression methods
- 2024-09-30: Add densification methods to survey
- 2024-09-17: Updated Morgenstern et al. results and reverted HAC results because of [confusion about testing conventions](https://github.com/YihangChen-ee/HAC/issues/14)
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12 changes: 7 additions & 5 deletions project-page/index_template.html
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Expand Up @@ -135,7 +135,7 @@ <h1 class="title is-1 publication-title">
<input type="checkbox" id="switchInputCD">
<span class="slider"></span>
</label>
<span class="switch-text right">Densification</span>
<span class="switch-text right">Compaction</span>
</div>
</div>

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<div class="selection-col">
<b style="margin-bottom: 5px; display: inline-block;">Methods:</b>
<label><input type="checkbox" class="row-toggle-c" checked>Compression</label>
<label><input type="checkbox" class="row-toggle-d">Densification</label>
<label><input type="checkbox" class="row-toggle-d">Compaction</label>
</div>
</div>
</div>
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<br>

The <b>ranks</b> represent the average rankings of the methods across all available and selected datasets.
The slider above the table allows you to toggle between ranking methods (compression and densification) as well
The slider above the table allows you to toggle between ranking methods (compression and compaction) as well
as pre-selected shown attributes, datasets, and methods.
Selections can be further refined using the checkboxes below the table.

<br>
<br>

While all selected datasets contribute to the compression rank, the densification rank is limited only
According to our definitions, the <b>compression rank</b> seeks the smallest file size for the highest possible quality,
while the <b>compaction rank</b> assesses the minimal number of Gaussians in relation to image quality.
While all selected datasets contribute to the compression rank, the compaction rank is limited only
to the Tanks and Temples, Mip-NeRF 360 and Deep Blending datasets.
The quality metrics <b>PSNR</b>, <b>SSIM</b>, and <b>LPIPS</b> are equally weighted with the <b>model size</b> for the compression rank,
and with the <b>number of Gaussians</b> for the densification rank.
and with the <b>number of Gaussians</b> for the compaction rank.

<br>
<br>
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