Segmentation Domain Adaptation¶
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 DALIB.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 |
