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Semantic Segmentation on Cityscapes (val) (mIoU, FPS, FLOPs, Params)

80.9mIoUPIDNet-L
74.24475.97277.779.428Jun 4, 2022

Evaluation results

MethodLinks
PIDNet-LGPU=RTX 3090, Resolution=2048×1024, inference_platform=Author Platform2022.0680.931.1275.8—
PIDNet-MGPU=RTX 3090, Resolution=2048×1024, inference_platform=Author Platform2022.0680.139.8197.4—
DDRNet-23GPU=RTX 3090, Resolution=2048×1024, inference_platform=Author Platform2022.0679.551.4143.1—
PIDNet-S-SimpleGPU=RTX 3090, Resolution=2048×1024, inference_platform=Author Platform2022.0678.8100.846.3—
PIDNet-SGPU=RTX 3090, Resolution=2048×1024, inference_platform=Author Platform2022.0678.893.247.6—
PP-LiteSeg-B2GPU=RTX 3090, Resolution=1536×768, inference_platform=Author Platform2022.0678.268.2——
HyperSeg-SGPU=RTX 3090, Resolution=1536×768, inference_platform=Author Platform2022.0678.245.71710.2
DDRNet-23-SGPU=RTX 3090, Resolution=2048×1024, inference_platform=Author Platform2022.0677.8108.136.3—
STDC2-Seg75GPU=RTX 3090, Resolution=1536×768, inference_platform=Author Platform2022.067758.2——
DF2-Seg2GPU=GTX 1080Ti, Resolution=1536×7682022.0676.956.3——
CABiNetGPU=RTX 2080Ti, Resolution=2048×10242022.0676.676.512—
HyperSeg-MGPU=RTX 3090, Resolution=1024×512, inference_platform=Author Platform2022.0676.259.17.510.1
PP-LiteSeg-T2GPU=RTX 3090, Resolution=1536×768, inference_platform=Author Platform2022.067696——
DF2-Seg1GPU=GTX 1080Ti, Resolution=1536×7682022.0675.967.2——
BiSeNetV2-LGPU=GTX 1080Ti, Resolution=1024×5122022.0675.847.3118.5—
SwiftNetRN-18GPU=GTX 1080Ti, Resolution=2048×10242022.0675.539.9104—
BiSeNet (Res18)GPU=GTX 1080Ti, Resolution=1536×7682022.0674.865.555.3—
STDC1-Seg75GPU=RTX 3090, Resolution=1536×768, inference_platform=Author Platform2022.0674.574.8——