# CNN Attention Enhanced ViT Network for Occluded Person Re-Identification
## 4 Results and Discussion
### Comparison with State-of-the-Art Methods
#### 4.3.2 Results for the Occluded Dataset  
The results of AET-Net on the Occluded-Duke dataset are presented in Table 3, along with those of other classic models for comparison. The Occluded-Duke images have more background clutter, occlusions, and other confusing features, which lead to lower accuracy for all models. However, the proposed AET-Net baseline model reported 54.5% mAP and 64.5% Rank-1 accuracy, outperforming the best partial model HOReID by 10.7% mAP and 9.4% Rank-1 and exceeding the best attention model PAT by 0.9% in mAP. In particular, AET-Net shows certain improvements compared to TransReID, DRL-Net, and PAT based on Transformer architecture. These outcomes suggest that our proposed AET-Net has improved the recognition performance and classification ability of the model.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline \multirow{2}{*}{**Types**} & \multirow{2}{*}{**Models**} & \multicolumn{2}{c}{**DukeMTMC**} & \multicolumn{2}{c}{**Market-1501**} \\  & & **mAP/\%** & **Rank-1/\%** & **mAP/\%** & **Rank-1/\%** \\ \hline \multirow{8}{*}{Partial Models} & Spindle [18] & - & - & - & 76.9 \\  & Part Aligned [34] & - & - & 63.4 & 81.0 \\  & PDC [19] & - & - & 63.4 & 84.1 \\  & DSR [35] & - & - & 64.2 & 83.6 \\  & MGCAM [16] & - & - & 74.3 & 83.8 \\  & Aligned Reid & - & - & 79.3 & 91.8 \\  & PGFA [7] & 65.5 & 82.6 & 76.8 & 91.2 \\  & PGFA-PE [51] & 72.6 & 86.2 & 81.3 & 92.7 \\  & PCB [22] & 66.1 & 81.8 & 77.4 & 92.3 \\  & PCB+RPP [22] & 69.2 & 83.3 & 81.6 & 93.8 \\  & HOReID [2] & 75.6 & 86.9 & 84.9 & 94.2 \\  & FPR [9] & 78.4 & 88.6 & 86.6 & 95.4 \\  & MGN [23] & 78.4 & 88.7 & 86.9 & 95.7 \\ \hline \multirow{8}{*}{Attention Models} & HACNN [38] & 63.8 & 80.5 & 82.8 & 93.8 \\  & MHN-6 [26] & 77.2 & 89.1 & 85.0 & 95.1 \\ \cline{1-1}  & CAM [33] & 72.9 & 85.8 & 84.5 & 94.7 \\ \cline{1-1}  & Part [8] & 78.2 & 88.8 & 88.0 & 95.4 \\ \cline{1-1}  & DRL-Net [5] & 76.6 & 88.1 & 86.9 & 94.7 \\ \cline{1-1}  & TransReID [24] & 79.3 & 88.8 & 86.8 & 94.7 \\ \hline Ours & AET-Net & 80.1 & 89.5 & 87.5 & 94.8 \\ \hline \hline \end{tabular}
\end{table}
Table 2: The performance comparison between our proposed model and state-of-the-art models on DukeMTMC and Market-1501.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Types**} & \multirow{2}{*}{**Models**} & \multicolumn{2}{c}{**Occluded-Duke**} \\  & & **mAP/\%** & **Rank-1/\%** \\ \hline \multirow{8}{*}{Partial Models} & Part Aligned [34] & 20.2 & 28.8 \\  & DSR [35] & 30.4 & 40.8 \\  & Ad-Occluded [4] & 32.2 & 44.5 \\  & PGFA [7] & 37.3 & 51.4 \\  & PCB [22] & 42.6 & 33.7 \\  & HOReID [2] & 43.8 & 55.1 \\  & PGFA-PE [51] & 43.5 & 56.6 \\ \hline \multirow{4}{*}{Attention Models} & HACNN [38] & 26.0 & 34.4 \\  & DRL-Net [5] & 50.8 & 65.0 \\ \cline{1-1}  & ISP [21] & 52.3 & 62.8 \\ \cline{1-1}  & PAT [8] & 53.6 & 64.5 \\ \cline{1-1}  & TransReID [24] & 53.1 & 60.5 \\ \hline Ours & AET-Net & 54.5 & 64.5 \\ \hline \hline \end{tabular}
\end{table}
Table 3: The performance comparison between our proposed model and state-of-the-art models on the Occluded-Duke.