Fully Convolutional Networks for Semantic Segmentation
Introduction
[ALGORITHM]
@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) |
download |
FCN |
R-50-D8 |
512x1024 |
40000 |
5.7 |
4.17 |
72.25 |
73.36 |
model | log |
FCN |
R-101-D8 |
512x1024 |
40000 |
9.2 |
2.66 |
75.45 |
76.58 |
model | log |
FCN |
R-50-D8 |
769x769 |
40000 |
6.5 |
1.80 |
71.47 |
72.54 |
model | log |
FCN |
R-101-D8 |
769x769 |
40000 |
10.4 |
1.19 |
73.93 |
75.14 |
model | log |
FCN |
R-18-D8 |
512x1024 |
80000 |
1.7 |
14.65 |
71.11 |
72.91 |
model | log |
FCN |
R-50-D8 |
512x1024 |
80000 |
- |
|
73.61 |
74.24 |
model | log |
FCN |
R-101-D8 |
512x1024 |
80000 |
- |
- |
75.13 |
75.94 |
model | log |
FCN |
R-18-D8 |
769x769 |
80000 |
1.9 |
6.40 |
70.80 |
73.16 |
model | log |
FCN |
R-50-D8 |
769x769 |
80000 |
- |
- |
72.64 |
73.32 |
model | log |
FCN |
R-101-D8 |
769x769 |
80000 |
- |
- |
75.52 |
76.61 |
model | log |
FCN |
R-18b-D8 |
512x1024 |
80000 |
1.6 |
16.74 |
70.24 |
72.77 |
model | log |
FCN |
R-50b-D8 |
512x1024 |
80000 |
5.6 |
4.20 |
75.65 |
77.59 |
model | log |
FCN |
R-101b-D8 |
512x1024 |
80000 |
9.1 |
2.73 |
77.37 |
78.77 |
model | log |
FCN |
R-18b-D8 |
769x769 |
80000 |
1.7 |
6.70 |
69.66 |
72.07 |
model | log |
FCN |
R-50b-D8 |
769x769 |
80000 |
6.3 |
1.82 |
73.83 |
76.60 |
model | log |
FCN |
R-101b-D8 |
769x769 |
80000 |
10.3 |
1.15 |
77.02 |
78.67 |
model | log |
ADE20K
Method |
Backbone |
Crop Size |
Lr schd |
Mem (GB) |
Inf time (fps) |
mIoU |
mIoU(ms+flip) |
download |
FCN |
R-50-D8 |
512x512 |
80000 |
8.5 |
23.49 |
35.94 |
37.94 |
model | log |
FCN |
R-101-D8 |
512x512 |
80000 |
12 |
14.78 |
39.61 |
40.83 |
model | log |
FCN |
R-50-D8 |
512x512 |
160000 |
- |
- |
36.10 |
38.08 |
model | log |
FCN |
R-101-D8 |
512x512 |
160000 |
- |
- |
39.91 |
41.40 |
model | log |
Pascal VOC 2012 + Aug
Method |
Backbone |
Crop Size |
Lr schd |
Mem (GB) |
Inf time (fps) |
mIoU |
mIoU(ms+flip) |
download |
FCN |
R-50-D8 |
512x512 |
20000 |
5.7 |
23.28 |
67.08 |
69.94 |
model | log |
FCN |
R-101-D8 |
512x512 |
20000 |
9.2 |
14.81 |
71.16 |
73.57 |
model | log |
FCN |
R-50-D8 |
512x512 |
40000 |
- |
- |
66.97 |
69.04 |
model | log |
FCN |
R-101-D8 |
512x512 |
40000 |
- |
- |
69.91 |
72.38 |
model | log |
Pascal Context
Method |
Backbone |
Crop Size |
Lr schd |
Mem (GB) |
Inf time (fps) |
mIoU |
mIoU(ms+flip) |
download |
FCN |
R-101-D8 |
480x480 |
40000 |
- |
9.93 |
44.14 |
45.67 |
model | log |
FCN |
R-101-D8 |
480x480 |
80000 |
- |
- |
44.47 |
45.74 |
model | log |