## 4 Experiments
### Experimental and Performance Analysis of BiResNeRF
#### 4.3.3 Results of BiResNeRF  
The experimental results include both quantitative (Table 2) and qualitative (Figure 7) comparisons between our method and BAA-NGP. Through observations and statistics during the experiment, the effectiveness of the stage transition signals and the smooth warm-up learning rate scheduling strategy has been validated.  
According to Table 2, our method performs well regarding pose estimation accuracy, rendering accuracy and training time. Among them, the average training time decreased by 34.96%, the average rotation error and translation error decreased by 34.66% and 39.73%, respectively, and the average rendering accuracy in terms of PSNR, SSIM and LPIPS increased by 4.90%, 0.96% and 18.14% respectively.  
Based on Table 3, it can be seen that there is an improvement in rotation error, translation error and the quality of the rendered photos. In terms of training time, it is reduced by 94.58% compared to BARF and 79.28% compared to NeRFAcc, which is equivalent to an acceleration of 18.44\(\times\) and 4\(\times\), respectively.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Scene**} & \multicolumn{3}{c}{**Camera Pose Registration**} & \multicolumn{6}{c}{**Visual Synthesis Quality**} & \multicolumn{3}{c}{**Training Time(s)**} \\  & **Rotation(*)\(\downarrow\)** & **Translation\(\downarrow\)** & **PSNR\(\uparrow\)** & **SSIM\(\uparrow\)** & **LPIPS\(\downarrow\)** & **RAFAcc** & **BARF** & **NeRFAcc** & **BARF** & **NeRFAcc** \\ \hline Lego & 0.077 & 0.059 & 0.257 & 0.215 & 28.377 & 30.020 & 0.929 & 0.948 & 0.048 & 0.038 & 9844 & 3647 \\ Chair & 0.095 & 0.074 & 0.396 & 0.334 & 31.202 & 32.361 & 0.955 & 0.965 & 0.044 & 0.039 & 9839 & 3440 \\ Drums & 0.051 & 0.038 & 0.201 & 0.191 & 23.914 & 24.772 & 0.900 & 0.917 & 0.099 & 0.079 & 12568 & 3532 \\ Ficus & 0.085 & 0.066 & 0.529 & 0.332 & 26.253 & 27.819 & 0.934 & 0.953 & 0.058 & 0.041 & 29349 & 3392 \\ Hottdog & 0.249 & 1.826 & 1.278 & 8.313 & 34.608 & 32.010 & 0.970 & 0.962 & 0.032 & 0.030 & 23485 & 3709 \\ Materials & 0.911 & 1.087 & 4.496 & 5.452 & 27.013 & 28.129 & 0.930 & 0.944 & 0.063 & 0.038 & 9839 & 3511 \\ Mic & 0.073 & 0.037 & 0.247 & 0.156 & 31.220 & 32.828 & 0.969 & 0.974 & 0.048 & 0.037 & 9803 & 3804 \\ Ship & 0.070 & 0.076 & 0.293 & 0.415 & 27.560 & 28.647 & 0.850 & 0.868 & 0.128 & 0.112 & 9907 & 4957 \\ mean & 0.202 & 0.408 & 0.962 & 1.926 & 28.768 & 29.573 & 0.930 & 0.941 & 0.065 & 0.052 & 14,329.250 & 3749.000 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Quantitative comparison of BiResNeRF with the baseline models BARF and NeRFAcc on Synthetic dataset. The translation error is the result of magnification by a factor of 100.  
\begin{table}
\begin{tabular}{l c c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Scene**} & \multicolumn{3}{c}{**Camera Pose Registration**} & \multicolumn{6}{c}{**Visual Synthesis Quality**} & \multicolumn{3}{c}{**Training Time(s)**} \\  & **Rotation(*)\(\downarrow\)** & **Translation\(\downarrow\)** & **PSNR\(\uparrow\)** & **SSIM\(\uparrow\)** & **LPIPS\(\downarrow\)** & **RAFAcc** & **BARF** & **NeRFAcc** \\ \hline Lego & 0.077 & 0.059 & 0.257 & 0.215 & 28.377 & 30.020 & 0.929 & 0.948 & 0.048 & 0.038 & 9844 & 3647 \\ Chair & 0.095 & 0.074 & 0.396 & 0.334 & 31.202 & 32.361 & 0.955 & 0.965 & 0.044 & 0.039 & 9839 & 34 Figure 7: Qualitative results on Synthetic dataset. GT (Ground Truth) represents reference images, while BAA refers to images rendered by the method in [33].