# Cross-View Attention Interaction Fusion Algorithm for Stereo Super-Resolution
## 3 Experimental Results
### Ablation Analysis
#### 3.2.1 Ablation Analysis of Attention Stereo Fusion Module  
On KITTI 2015 and Middlebury datasets, the pre-trained single image super-resolution network VDSR [8] was used as the upper and lower branches for ablation experiments. For fair comparison, only the vertical sparse connection included in the enhanced cross-view interaction strategy was used. The results are shown in Table 1, and where PA represents parallax attention block, PA + TA represents attention stereo fusion module, PA + CA represents attention module combined with parallax and channel and \(l\) represents the number of times inserted into the super-resolution branch of a single image where \(l\) is set to one, two and three, respectively.  
As can be seen from Table 1, for KITTI 2015 and Middlebury datasets, the results calculated by PA + TA_\(l\) are higher than those calculated by PA_\(l\) where the PSNR/SSIM calculated by PA + TA_\(3\) are 25.19 dB/0.854 and 28.15 dB/0.887, respectively. After embedding the attention stereo fusion module (PA + TA_\(3\) in VDSR, the performance is significantly improved compared with PA + TA_\(3\). Specifically, the PSNR gain is 0.10 dB, the SSIM gains are 0.01 and 0.003, respectively. It can be proved that the proposed attention stereo fusion module is conducive to the multiple aspects of learning between stereo images and enhances the consistency of stereo image pairs by strengthening the multibranch communication between the channel and the two dimensions of image (height and width). In addition, the number of times the attention stereo fusion module is inserted in the single  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Setting of Attention Module**} & \multicolumn{2}{c}{**KITTI 2015**} & \multicolumn{2}{c}{**Middlebury**} \\ \cline{2-5}  & **PSNR (dB)** & **SSIM** & **PSNR (dB)** & **SSIM** \\ \hline PA\_1 & 24.98 & 0.849 & 27.94 & 0.886 \\ PA\_2 & 25.02 & 0.849 & 27.95 & 0.886 \\ PA\_3 & 25.10 & 0.850 & 28.00 & 0.886 \\ (PA + CA)\_1 & 25.12 & 0.851 & 28.04 & 0.886 \\ (PA + CA)\_2 & 25.16 & 0.851 & 28.10 & 0.886 \\ (PA + CA)\_3 & 25.19 & 0.854 & 28.15 & 0.887 \\ (PA + TA)\_1 & 25.14 & 0.851 & 28.11 & 0.886 \\ (PA + TA)\_2 & 25.23 & 0.856 & 28.21 & 0.886 \\ (PA + TA)\_3 & 25.29 & 0.861 & 28.28 & 0.890 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Ablation experiment on attention stereo fusion module.  
image super-resolution branch also determines the performance gain. It can be seen from the Table 1 that with the increase of the number of times, the performance will improve uniformly, but the improvement range will decrease step by step. Therefore, in order to significantly improve the performance gain within a reasonable computing overhead, the number of insertions times is set to 3. In other words, compared with the parallax attention module, our proposed attention stereo fusion module can more compactly realize the bidirectional information transmission of left and right images, further providing basis for multiple information interaction between two perspective images.