• Laser & Optoelectronics Progress
  • Vol. 56, Issue 24, 241005 (2019)
Shiyi Yue*
Author Affiliations
  • School of Electrical and Information Engineering, Tianjin University, Tianjin 300072, China
  • show less
    DOI: 10.3788/LOP56.241005 Cite this Article Set citation alerts
    Shiyi Yue. Image Semantic Segmentation Based on Hierarchical Context Information[J]. Laser & Optoelectronics Progress, 2019, 56(24): 241005 Copy Citation Text show less
    Hierarchical context information network architecture
    Fig. 1. Hierarchical context information network architecture
    Position attention mechanism model
    Fig. 2. Position attention mechanism model
    Dilated convolution model
    Fig. 3. Dilated convolution model
    Enhance model
    Fig. 4. Enhance model
    Network structure of baseline[16]
    Fig. 5. Network structure of baseline[16]
    Network structure of ours-1
    Fig. 6. Network structure of ours-1
    Network structure of ours-2
    Fig. 7. Network structure of ours-2
    Network structure of ours-3
    Fig. 8. Network structure of ours-3
    Qualitative comparison between baseline and ours-4
    Fig. 9. Qualitative comparison between baseline and ours-4
    MethodWith/without modelMiou /%
    PAMDCM-4DCM-3EMCCM
    Baseline59.82
    Ours-160.73
    Ours-261.16
    Ours-361.78
    Ours-462.11
    Table 1. Performance of each model on Cityscapes validation set
    MethodAccuracyMiou
    RoaSidBuiWalFenPolTLiTSiVegTerSkyPerRidCarTruBusTraMotBic
    Base-line96.572.485.838.135.730.641.750.686.358.990.465.245.888.055.164.549.836.351.960.17
    Ours-296.773.586.138.236.833.342.751.387.161.191.666.147.890.354.867.250.336.753.061.30
    Ours-396.773.086.444.237.530.741.551.587.458.491.766.947.390.556.668.056.940.352.461.99
    Ours-496.974.586.744.238.231.242.852.187.859.791.766.748.390.455.165.455.840.553.562.19
    Table 2. Performance of each model on Cityscapes test set%
    ModelBackboneMiou /%
    Val setTest set
    Baseline*ResNet-5076.34-
    BaselineResNet-5075.81-
    Ours-4ResNet-5077.20-
    Deeplab-V2[10]ResNet-101-70.40
    Refinenet[20]ResNet-101-73.60
    Gcn[14]ResNet-101-76.90
    BaselineResNet-50-75.46
    Ours-4ResNet-50-76.73
    BaselineResNet-101-76.67
    Ours-4ResNet-101-78.01
    Table 3. Network performance on Cityscapes dataset