Image Segmentation
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upernet
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GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond

Introduction

[ALGORITHM]

@inproceedings{cao2019gcnet,
  title={Gcnet: Non-local networks meet squeeze-excitation networks and beyond},
  author={Cao, Yue and Xu, Jiarui and Lin, Stephen and Wei, Fangyun and Hu, Han},
  booktitle={Proceedings of the IEEE International Conference on Computer Vision Workshops},
  pages={0--0},
  year={2019}
}

Results and models

Cityscapes

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
GCNet R-50-D8 512x1024 40000 5.8 3.93 77.69 78.56 model | log
GCNet R-101-D8 512x1024 40000 9.2 2.61 78.28 79.34 model | log
GCNet R-50-D8 769x769 40000 6.5 1.67 78.12 80.09 model | log
GCNet R-101-D8 769x769 40000 10.5 1.13 78.95 80.71 model | log
GCNet R-50-D8 512x1024 80000 - - 78.48 80.01 model | log
GCNet R-101-D8 512x1024 80000 - - 79.03 79.84 model | log
GCNet R-50-D8 769x769 80000 - - 78.68 80.66 model | log
GCNet R-101-D8 769x769 80000 - - 79.18 80.71 model | log

ADE20K

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
GCNet R-50-D8 512x512 80000 8.5 23.38 41.47 42.85 model | log
GCNet R-101-D8 512x512 80000 12 15.20 42.82 44.54 model | log
GCNet R-50-D8 512x512 160000 - - 42.37 43.52 model | log
GCNet R-101-D8 512x512 160000 - - 43.69 45.21 model | log

Pascal VOC 2012 + Aug

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
GCNet R-50-D8 512x512 20000 5.8 23.35 76.42 77.51 model | log
GCNet R-101-D8 512x512 20000 9.2 14.80 77.41 78.56 model | log
GCNet R-50-D8 512x512 40000 - - 76.24 77.63 model | log
GCNet R-101-D8 512x512 40000 - - 77.84 78.59 model | log