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Fully Convolutional Networks for Semantic Segmentation

Introduction 

@article{shelhamer2017fully,
  title={Fully convolutional networks for semantic segmentation},
  author={Shelhamer, Evan and Long, Jonathan and Darrell, Trevor},
  journal={IEEE transactions on pattern analysis and machine intelligence},
  volume={39},
  number={4},
  pages={640--651},
  year={2017},
  publisher={IEEE Trans Pattern Anal Mach Intell}
}

Results and models

Cityscapes

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
FCN R-50-D8 512x1024 40000 5.7 4.17 72.25 73.36 config model | log
FCN R-101-D8 512x1024 40000 9.2 2.66 75.45 76.58 config model | log
FCN R-50-D8 769x769 40000 6.5 1.80 71.47 72.54 config model | log
FCN R-101-D8 769x769 40000 10.4 1.19 73.93 75.14 config model | log
FCN R-18-D8 512x1024 80000 1.7 14.65 71.11 72.91 config model | log
FCN R-50-D8 512x1024 80000 - 73.61 74.24 config model | log
FCN R-101-D8 512x1024 80000 - - 75.13 75.94 config model | log
FCN R-18-D8 769x769 80000 1.9 6.40 70.80 73.16 config model | log
FCN R-50-D8 769x769 80000 - - 72.64 73.32 config model | log
FCN R-101-D8 769x769 80000 - - 75.52 76.61 config model | log
FCN R-18b-D8 512x1024 80000 1.6 16.74 70.24 72.77 config model | log
FCN R-50b-D8 512x1024 80000 5.6 4.20 75.65 77.59 config model | log
FCN R-101b-D8 512x1024 80000 9.1 2.73 77.37 78.77 config model | log
FCN R-18b-D8 769x769 80000 1.7 6.70 69.66 72.07 config model | log
FCN R-50b-D8 769x769 80000 6.3 1.82 73.83 76.60 config model | log
FCN R-101b-D8 769x769 80000 10.3 1.15 77.02 78.67 config model | log
FCN-D6 R-50-D16 512x1024 40000 3.4 10.22 77.06 78.85 config model | log
FCN-D6 R-50-D16 512x1024 80000 - 10.35 77.27 78.88 config model | log
FCN-D6 R-50-D16 769x769 40000 3.7 4.17 76.82 78.22 config model | log
FCN-D6 R-50-D16 769x769 80000 - 4.15 77.04 78.40 config model | log
FCN-D6 R-101-D16 512x1024 40000 4.5 8.04 77.36 79.18 config model | log
FCN-D6 R-101-D16 512x1024 80000 - 8.26 78.46 80.42 config model | log
FCN-D6 R-101-D16 769x769 40000 5.0 3.12 77.28 78.95 config model | log
FCN-D6 R-101-D16 769x769 80000 - 3.21 78.06 79.58 config model | log
FCN-D6 R-50b-D16 512x1024 80000 3.2 10.16 76.99 79.03 config model | log
FCN-D6 R-50b-D16 769x769 80000 3.6 4.17 76.86 78.52 config model | log
FCN-D6 R-101b-D16 512x1024 80000 4.3 8.46 77.72 79.53 config model | log
FCN-D6 R-101b-D16 769x769 80000 4.8 3.32 77.34 78.91 config model | log

ADE20K

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
FCN R-50-D8 512x512 80000 8.5 23.49 35.94 37.94 config model | log
FCN R-101-D8 512x512 80000 12 14.78 39.61 40.83 config model | log
FCN R-50-D8 512x512 160000 - - 36.10 38.08 config model | log
FCN R-101-D8 512x512 160000 - - 39.91 41.40 config model | log

Pascal VOC 2012 + Aug

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
FCN R-50-D8 512x512 20000 5.7 23.28 67.08 69.94 config model | log
FCN R-101-D8 512x512 20000 9.2 14.81 71.16 73.57 config model | log
FCN R-50-D8 512x512 40000 - - 66.97 69.04 config model | log
FCN R-101-D8 512x512 40000 - - 69.91 72.38 config model | log

Pascal Context

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
FCN R-101-D8 480x480 40000 - 9.93 44.43 45.63 config model | log
FCN R-101-D8 480x480 80000 - - 44.13 45.26 config model | log

Pascal Context 59

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) config download
FCN R-101-D8 480x480 40000 - - 48.42 50.4 config model | log
FCN R-101-D8 480x480 80000 - - 49.35 51.38 config model | log