Semantic Segmentation¶
We provide benchmarks of different segmentation domain adaptation algorithms on GTA5->Cityscapes and Synthia->Cityscapes as follows. Those domain adaptation algorithms includes:
Note
Originmeans the accuracy reported by the original paper.mIoUis the mean IoU reported by Transfer-Learn.Src Onlyrefers to the model trained with data from the source domain.Oraclerefers to the model trained with data from the target domain.
GTA5->Cityscapes mIoU on deeplabv2 (ResNet-101)¶
Methods |
Origin |
mIoU |
road |
sidewalk |
building |
wall |
fence |
pole |
light |
sign |
veg |
Src Only |
27.1 |
37.3 |
66.5 |
17.4 |
73.3 |
13.4 |
21.5 |
22.8 |
30.1 |
17.1 |
82.2 |
CycleGAN |
/ |
47.0 |
88.4 |
41.9 |
83.6 |
34.4 |
23.9 |
32.9 |
35.5 |
26.0 |
83.1 |
Cycada |
42.7 |
47.4 |
87.3 |
35.7 |
83.7 |
31.3 |
24.0 |
32.2 |
35.8 |
30.3 |
82.7 |
ADVENT |
43.8 |
43.8 |
89.3 |
33.9 |
80.3 |
24.0 |
25.2 |
27.8 |
36.7 |
18.2 |
84.3 |
FDA |
44.6 |
45.6 |
85.5 |
31.7 |
81.8 |
27.1 |
24.9 |
28.9 |
38.1 |
23.2 |
83.7 |
Oracle |
65.1 |
70.5 |
97.4 |
79.7 |
90.1 |
53.0 |
50.0 |
48.0 |
55.5 |
67.2 |
90.2 |
Methods |
terrain |
sky |
person |
rider |
car |
truck |
bus |
train |
mbike |
bike |
Src Only |
7.1 |
73.6 |
57.4 |
28.4 |
78.6 |
36.1 |
13.4 |
1.5 |
31.9 |
36.2 |
CycleGAN |
36.8 |
82.3 |
59.9 |
27.0 |
83.4 |
31.6 |
42.3 |
11.0 |
28.2 |
40.5 |
Cycada |
32.0 |
85.7 |
60.8 |
31.5 |
85.6 |
39.8 |
43.3 |
5.4 |
29.5 |
44.6 |
ADVENT |
33.9 |
81.3 |
59.8 |
28.4 |
84.3 |
34.1 |
44.4 |
0.1 |
33.2 |
12.9 |
FDA |
40.3 |
80.6 |
60.5 |
30.3 |
79.1 |
32.8 |
45.1 |
5.0 |
32.4 |
35.2 |
Oracle |
60.0 |
93.0 |
72.7 |
55.2 |
92.7 |
76.5 |
78.5 |
56.0 |
54.6 |
68.8 |
Synthia->Cityscapes mIoU on deeplabv2 (ResNet-101)¶
Methods |
Origin |
mIoU |
road |
sidewalk |
building |
light |
sign |
veg |
sky |
person |
rider |
car |
bus |
mbike |
bike |
Src Only |
22.1 |
41.5 |
59.6 |
21.1 |
77.4 |
7.7 |
17.6 |
78.0 |
84.5 |
53.2 |
16.9 |
65.9 |
24.9 |
8.5 |
24.8 |
ADVENT |
47.6 |
47.9 |
88.3 |
44.9 |
80.5 |
4.5 |
9.1 |
81.3 |
86.2 |
52.9 |
21.0 |
82.0 |
30.3 |
11.9 |
30.2 |
FDA |
/ |
43.9 |
62.5 |
23.7 |
78.5 |
9.4 |
15.7 |
78.3 |
81.1 |
52.3 |
18.7 |
79.8 |
32.5 |
8.7 |
29.6 |
Oracle |
71.7 |
76.6 |
97.4 |
79.7 |
90.1 |
55.5 |
67.2 |
90.2 |
93.0 |
72.7 |
55.2 |
92.7 |
78.5 |
54.6 |
68.8 |
Cityscapes->Foggy Cityscapes mIoU on deeplabv2 (ResNet-101)¶
Methods |
mIoU |
road |
sidewalk |
building |
wall |
fence |
pole |
light |
sign |
veg |
Src Only |
51.2 |
95.3 |
70.2 |
64.1 |
31.9 |
35.2 |
30.7 |
33.3 |
51.1 |
42.3 |
CycleGAN |
66.0 |
97.1 |
77.6 |
84.3 |
42.7 |
46.3 |
42.8 |
47.5 |
61.0 |
84.0 |
Cycada |
63.3 |
96.8 |
75.5 |
79.1 |
38.0 |
40.3 |
42.1 |
48.2 |
61.2 |
76.9 |
ADVENT |
61.8 |
96.8 |
75.1 |
76.4 |
46.2 |
42.6 |
39.3 |
43.6 |
58.9 |
74.3 |
FDA |
61.9 |
96.9 |
77.2 |
75.3 |
46.5 |
42.0 |
39.8 |
47.1 |
61.0 |
72.7 |
Oracle |
66.9 |
97.4 |
78.6 |
88.1 |
50.7 |
50.5 |
46.2 |
51.3 |
64.4 |
88.1 |
Methods |
terrain |
sky |
person |
rider |
car |
truck |
bus |
train |
mbike |
bike |
Src Only |
44.0 |
32.1 |
64.4 |
47.0 |
86.0 |
64.4 |
56.4 |
21.1 |
43.1 |
60.8 |
CycleGAN |
55.2 |
83.4 |
69.4 |
51.8 |
90.7 |
73.7 |
76.2 |
54.2 |
50.7 |
65.6 |
Cycada |
52.1 |
77.6 |
68.6 |
51.7 |
90.4 |
71.7 |
70.4 |
43.3 |
52.6 |
65.7 |
ADVENT |
50.1 |
75.9 |
67.3 |
51.0 |
89.4 |
70.5 |
64.7 |
39.9 |
47.9 |
65.0 |
FDA |
54.6 |
63.8 |
68.4 |
50.1 |
90.1 |
72.8 |
68.0 |
35.5 |
50.8 |
64.2 |
Oracle |
55.3 |
87.4 |
70.9 |
52.7 |
91.6 |
72.4 |
73.2 |
31.8 |
52.2 |
67.4 |
