Image Segmentation
Transformers
PyTorch
upernet
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Rethinking atrous convolution for semantic image segmentation

Introduction

[ALGORITHM]

@article{chen2017rethinking,
  title={Rethinking atrous convolution for semantic image segmentation},
  author={Chen, Liang-Chieh and Papandreou, George and Schroff, Florian and Adam, Hartwig},
  journal={arXiv preprint arXiv:1706.05587},
  year={2017}
}

Results and models

Note: D-8 here corresponding to the output stride 8 setting for DeepLab series.

Cityscapes

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
DeepLabV3 R-50-D8 512x1024 40000 6.1 2.57 79.09 80.45 model | log
DeepLabV3 R-101-D8 512x1024 40000 9.6 1.92 77.12 79.61 model | log
DeepLabV3 R-50-D8 769x769 40000 6.9 1.11 78.58 79.89 model | log
DeepLabV3 R-101-D8 769x769 40000 10.9 0.83 79.27 80.11 model | log
DeepLabV3 R-18-D8 512x1024 80000 1.7 13.78 76.70 78.27 model | log
DeepLabV3 R-50-D8 512x1024 80000 - - 79.32 80.57 model | log
DeepLabV3 R-101-D8 512x1024 80000 - - 80.20 81.21 model | log
DeepLabV3 R-18-D8 769x769 80000 1.9 5.55 76.60 78.26 model | log
DeepLabV3 R-50-D8 769x769 80000 - - 79.89 81.06 model | log
DeepLabV3 R-101-D8 769x769 80000 - - 79.67 80.81 model | log
DeepLabV3 R-101-D16-MG124 512x1024 40000 4.7 - 6.96 76.71 78.63 model | log
DeepLabV3 R-101-D16-MG124 512x1024 80000 - - 78.36 79.84 model | log
DeepLabV3 R-18b-D8 512x1024 80000 1.6 13.93 76.26 77.88 model | log
DeepLabV3 R-50b-D8 512x1024 80000 6.0 2.74 79.63 80.98 model | log
DeepLabV3 R-101b-D8 512x1024 80000 9.5 1.81 80.01 81.21 model | log
DeepLabV3 R-18b-D8 769x769 80000 1.8 5.79 76.63 77.51 model | log
DeepLabV3 R-50b-D8 769x769 80000 6.8 1.16 78.80 80.27 model | log
DeepLabV3 R-101b-D8 769x769 80000 10.7 0.82 79.41 80.73 model | log

ADE20K

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
DeepLabV3 R-50-D8 512x512 80000 8.9 14.76 42.42 43.28 model | log
DeepLabV3 R-101-D8 512x512 80000 12.4 10.14 44.08 45.19 model | log
DeepLabV3 R-50-D8 512x512 160000 - - 42.66 44.09 model | log
DeepLabV3 R-101-D8 512x512 160000 - - 45.00 46.66 model | log

Pascal VOC 2012 + Aug

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
DeepLabV3 R-50-D8 512x512 20000 6.1 13.88 76.17 77.42 model | log
DeepLabV3 R-101-D8 512x512 20000 9.6 9.81 78.70 79.95 model | log
DeepLabV3 R-50-D8 512x512 40000 - - 77.68 78.78 model | log
DeepLabV3 R-101-D8 512x512 40000 - - 77.92 79.18 model | log

Pascal Context

Method Backbone Crop Size Lr schd Mem (GB) Inf time (fps) mIoU mIoU(ms+flip) download
DeepLabV3 R-101-D8 480x480 40000 9.2 7.09 46.55 47.81 model | log
DeepLabV3 R-101-D8 480x480 80000 - - 46.42 47.53 model | log