# High-Fold 3D Gaussian Splitting Model Pruning Method Assisted by Opacity
## 4 Experiments
### Performance Evaluation
\begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Scene** & **M60** & **Playground** & **Train** & **Truck** & **Family** & **Horse** & **Lighthouse** \\ \hline \multirow{4}{*}{3 DGS} & PSNR & 28.991 & 26.985 & 22.804 & 26.597 & 25.116 & 24.393 & 22.142 \\  & SSIM & 0.925 & 0.902 & 0.874 & 0.907 & 0.877 & 0.891 & 0.839 \\  & LPIPS & 0.125 & 0.146 & 0.187 & 0.134 & 0.165 & 0.165 & 0.222 \\  & Size & 291M & 352M & 186M & 380M & 506M & 298M & 202M \\ \hline \multirow{4}{*}{Ours} & PSNR & 26.397 & 25.428 & 21.615 & 25.702 & 24.553 & 23.781 & 21.593 \\  & SSIM & 0.872 & 0.833 & 0.773 & 0.879 & 0.849 & 0.868 & 0.792 \\  & LPIPS & 0.218 & 0.239 & 0.304 & 0.191 & 0.225 & 0.209 & 0.326 \\  & Size & **7.53M** & **10.79M** & **4.89M** & **11.47M** & **23M** & **15M** & **5.3M** \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Comparative experimental results of Tanks & Temples sub-dataset. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Scene** & **Bicycle** & **Flower** & **Garden** & **Stump** & **Treehill** & **Room** & **Counter** & **Kitchen** & **Bonsai** \\ \hline \multirow{4}{*}{3 DGS} & PSNR & 25.19 & 21.32 & 27.31 & 26.60 & 22.51 & 31.46 & 29.15 & 31.63 & 32.89 \\  & SSIM & 0.752 & 0.586 & 0.858 & 0.767 & 0.631 & 0.920 & 0.913 & 0.932 & 0.947 \\  & LPIPS & 0.237 & 0.364 & 0.121 & 0.242 & 0.352 & 0.201 & 0.181 & 0.114 & 0.171 \\  & Size & 1433.6M & 806M & 1331.2M & 1126.4M & 820.2M & 350M & 274M & 417M & 248M \\ \hline \multirow{4}{*}{Light- gaussian} & PSNR & 25.06 & 20.25 & 26.62 & 26.76 & 22.60 & 31.17 & 28.36 & 30.96 & 31.45 \\  & SSIM & 0.745 & 0.569 & 0.842 & 0.774 & 0.628 & 0.917 & 0.899 & 0.921 & 0.938 \\  & LPIPS & 0.257 & 0.412 & 0.167 & 0.251 & 0.372 & 0.214 & 0.218 & 0.162 & 0.196 \\  & Size & 55.84M & 45.31M & 55.65M & 48.46M & 52.60M & 30.36M & 30.44M & 39.41M & 31.42M \\ \hline \multirow{4}{*}{C3 dgs} & PSNR & 25.23 & 20.89 & 26.74 & 26.42 & 22.65 & 30.96 & 27.91 & 30.86 & 31.97 \\  & SSIM & 0.726 & 0.565 & 0.832 & 0.759 & 0.634 & 0.903 & 0.885 & 0.907 & 0.941 \\  & LPIPS & 0.264 & 0.390 & 0.143 & 0.294 & 0.374 & 0.244 & 0.213 & 0.186 & 0.187 \\  & Size & 62.98M & 52.16M & 69.78M & 56.74M & 57.12M & 34.86M & 35.76M & 46.53M & 37.48M \\ \hline \multirow{4}{*}{Ours} & PSNR & 24.45 & 19.81 & 25.50 & 25.69 & 21.03 & 28.62 & 26.89 & 29.77 & 30.42 \\  & SSIM & 0.675 & 0.514 & 0.769 & 0.714 & 0.683 & 0.843 & 0.853 & 0.857 & 0.896 \\ \cline{1-1}  & LPIPS & 0.308 & 0.429 & 0.234 & 0.338 & 0.437 & 0.279 & 0.279 & 0.248 & 0.230 \\ \cline{1-1}  & Size & **32.22M** & **14.94M** & **26.08M** & **29.16M** & **16.68M** & **7.66M** & **6.75M** & **6.41M** & **8.09M** \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparative experimental results of MIP-NeRF 360 sub-dataset. significant distortion or deformation in the overall structure, and the renderings retain satisfactory visual quality. However, in areas with dense details and subtle color variations, the renderings from our model appear somewhat blurred, as demonstrated by the depiction of grass in Figure 4. The results of our analysis suggest that this phenomenon can be attributed to the compression strategy employed by our model, which adheres to a pruning principle and exhibits low tolerance for small Gaussian points during training. As a result, Gaussian points corresponding to areas with rapid color changes may be excessively pruned. This over-pruning of Gaussian points leads to a substantial degradation in reconstruction quality, which is reflected in the blurring and distortion observed in the rendered images. The garden dataset shown in Figure 4 further highlights that our compression model requires refinement, particularly in rendering regions with significant gloss changes. Nevertheless, in terms of overall image rendering, our model still achieves commendable visual expression effects. Figure 5 compares the visualization with the Lightgaussian method. Figure 4: Visualization of the reconstructed results.