Research Article
[Retracted] DARSegNet: A Real-Time Semantic Segmentation Method Based on Dual Attention Fusion Module and Encoder-Decoder Network
Table 4
Comparison of accuracy, speed, and parameters of the lightweight segmentation model on the CamVid test set.
| Method | Pretraining | GPU | MIoU (%) | Speed (FPS) |
| SegNet | ImageNet | TitanX | 55.6 | 15 | ENet | No | TitanX | 51.3 | 61.2 | BiseNet | ImageNet | 1080Ti | 65.6 | 175 | ICNet | ImageNet | TitanX | 67.1 | 34.5 | SFNet (DF2) | No | 1080Ti | 70.4 | 134 | CAS | No | Titan Xp | 71.2 | 169 | BiSeNet V2 | No | 1080Ti | 68.7 | 116 | BiSeNet V2 | No | 1080Ti | 73.2 | 32.7 | SwiftNet | No | 1080Ti | 72.6 | 75.9 | DARSegNet (ours) | No | 1080Ti | 73.27 | 109 | DARSegNet (ours) | ImageNet | 1080Ti | 73.96 | 109 |
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The best results in each class are shown in bold.
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