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Semantic Segmentation on CamVid 12 classes (test)

70mIoU (T367)IkshanaNet-12G
58.14461.22264.367.378Jan 21, 2021

Evaluation results

MethodLinks
IkshanaNet-12GBackbone=IkshanaNet-12G, Param(M)=6.5, GFLOPS=285.02021.017067.160.665.9
U-NetBackbone=U-Net, Param(M)=31.0, GFLOPS=130.02021.0169.562.861.664.6
IkshanaNet-MBackbone=IkshanaNet-M, Param(M)=4.0, GFLOPS=139.02021.0168.562.958.863.4
EfficientNet-b1Backbone=EfficientNet-b1, Param(M)=7.4, GFLOPS=1.52021.0168.461.358.862.8
IkshanaNet-6GBackbone=IkshanaNet-6G, Param(M)=1.8, GFLOPS=82.02021.0167.865.96064.6
IkshanaNet-3GBackbone=IkshanaNet-3G, Param(M)=0.5, GFLOPS=26.02021.0165.762.561.263.1
EfficientNet-b6Backbone=EfficientNet-b6, Param(M)=42.0, GFLOPS=1.92021.016557.860.461
ResNet-18Backbone=ResNet-18, Param(M)=12.3, GFLOPS=12.42021.0164.963.756.661.7
RegNetY-08Backbone=RegNetY-08, Param(M)=7.0, GFLOPS=5.82021.0164.361.457.861.2
EfficientNet-b4Backbone=EfficientNet-b4, Param(M)=18.6, GFLOPS=1.72021.0164.162.260.562.3
MobileNet-V2Backbone=MobileNet-V2, Param(M)=4.4, GFLOPS=4.12021.0163.956.154.658.2
ResNet-101Backbone=ResNet-101, Param(M)=59.3, GFLOPS=59.92021.0163.856.455.758.6
HRNet-V2Backbone=HRNet-V2, Param(M)=65.9, GFLOPS=63.52021.0163.662.95560.5
ResNext-50Backbone=ResNext-50, Param(M)=26.2, GFLOPS=25.02021.0162.656.154.657.8
RegNetY-40Backbone=RegNetY-40, Param(M)=21.5, GFLOPS=18.82021.01626159.260.7
RegNetY-80Backbone=RegNetY-80, Param(M)=40.3, GFLOPS=34.42021.016263.853.859.9
ResNet-50Backbone=ResNet-50, Param(M)=26.7, GFLOPS=25.02021.0161.660.355.959.3
DenseNet-161Backbone=DenseNet-161, Param(M)=43.2, GFLOPS=43.62021.0158.657.853.856.7