# Matchability and Uncertainty-Aware Iterative Disparity Refinement for Stereo Matching
## 4 Experiments
### Ablation Study  
Ablation experiments are performed on the proposed MUIR pre-trained model to discuss the effectiveness of the proposed MUD, UFI and MGA modules. The detailed quantitative evaluation results are reported in Table 1. It should be noted that due to the absence of ill-posed region labels, the model performance in occluded regions is evaluated as an approximation. The occlusion labels are obtained from the warping error between left and right view disparities. The warping error occurs when sampling the right view's disparity based on the left view's disparity, resulting in a warped disparity. A point is marked as occluded when this warping error exceeds a certain threshold. The EPE and Bad1.0 metrics are divided into all pixels (All), non-occluded pixels (Noc) and occluded pixels (Occ). The absolute prediction error (APE) and the area under the sparsification error curve (AUSE) are calculated to quantitatively evaluate the numerical and distributional accuracy of the estimated uncertainty.  
The proposed MUIR fast and MUIR pre-trained models are evaluated in rows 7 and 11 of Table 1. Compared to the baseline (rows 1, 8), the disparity EPE is reduced by about 17.9% and 17.4%, respectively, and the A50 is reduced by about 45% and 34.2%, respectively, indicating a lower and more concentrated distributed disparity error. In addition, the Bad1.0 in occluded regions is reduced by about 16.9% and 16%, indicating the improved robustness of MUIR for ill-posed regions.  
\begin{table}
\begin{tabular}{c l c c c c c c c c c c} \hline \hline  & \multicolumn{1}{c}{**Models 1**} & \multicolumn{1}{c}{**Param**} & \multicolumn{1}{c}{**Time**} & \multicolumn{3}{c}{**EPE (px)**} & \multicolumn{3}{c}{**A50**} & \multicolumn{3}{c}{**Bad1.0 (\%)**} & \multicolumn{1}{c}{**APE**} & \multicolumn{1}{c}{**AUSE**} \\  & \multicolumn{1}{c}{**(M)**} & \multicolumn{1}{c}{**(s)**} & \multicolumn{1}{c}{**All**} & \multicolumn{1}{c}{**Noc**} & \multicolumn{1}{c}{**Occ**} & \multicolumn{1}{c}{**(px)**} & \multicolumn{1}{c}{**All**} & \multicolumn{1}{c}{**Noc**} & \multicolumn{1}{c}{**Occ**} & \multicolumn{1}{c}{**(px)**} & \multicolumn{1}{c}{**(px)**} & \multicolumn{1}{c}{**(px)**} \\ \hline (1) & Baseline fast [12] & 9.86 & 0.052 & 0.866 & 0.544 & 2.523 & 0.180 & 9.573 & 6.142 & 28.890 & - & - \\ (2) & +Simple uncertainty [17] & 10.17 & 0.041 & 1.077 & 0.557 & 3.325 & 0.161 & 9.910 & 6.339 & 30.010 & 0.820 & 5.113 \\ (3) & +Ours uncertainty & 10.32 & 0.040 & 0.911 & 0.544 & 2.646 & 0.207 & 9.354 & 5.935 & 28.618 & 0.482 & 5.598 \\ (4) & +MUD & 10.30 & 0.050 & 0.797 & 0.494 & 2.378 & 0.127 & 8.390 & 5.287 & 25.728 & 0.433 & 5.042 \\ (5) & +MUD+UFI & 12.89 & 0.059 & 0.766 & 0.456 & 2.328 & 0.131 & 8.010 & 4.963 & 24.927 & 0.423 & 4.872 \\ (6) & +MUD+UFI+GMA [48] & 13.64 & 0.065 & 0.731 & **0.436** & 2.215 & 0.124 & 7.779 & **4.794** & 24.339 & **0.405** & **4.768** \\ (7) & MUIR fast & 14.00 & 0.066 & **0.711** & 0.461 & **2.144** & **0.099** & **7.769** & 4.853 & **24.002** & **0.405** & 4.977 \\ (7) & (+MUD+UFI+MGA) & 14.00 & 0.066 & **0.711** & 0.461 & **2.144** & **0.099** & **7.769** & 4.853 & **24.002** & **0.405** & 4.977 \\ \hline (8) & Baseline [12] & 11.11 & 0.215 & 0.690 & 0.406 & 2.075 & 0.155 & 7.255 & 4.304 & 23.366 & - & - \\ (9) & +MUD & 12.92 & 0.222 & 0.643 & 0.367 & 1.956 & 0.135 & 6.197 & 3.554 & 20.705 & 0.253 & 3.497 \\ (10) & +MUD+UFI & 15.95 & 0.268 & 0.617 & 0.351 & 1.917 & 0.120 & 5.957 & 3.389 & 20.063 & 0.248 & **3.289** \\ (11) &
\begin{tabular}{c} MUIR \\ (+MUD+UFI+MGA) \\ \end{tabular} & 17.15 & 0.295 & **0.570** & **0.325** & **1.767** & **0.102** & **5.819** & **3.302** & **19.618** & **0.236** & 3.493 \\ \hline \hline \end{tabular}  
* These results were measured with maximum disparity set to 192 pixels following [12].  
\end{table}
Table 1: Ablation study on the proposed MUIR. The evaluation is conducted on the held-out Scene Flow [21] test set 1. Rows (1–7) and rows (8–11) contain models performed at 1/8 and 1/4 resolution, respectively. The best results in each category are bolded.