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Semantic Segmentation on Paris-Lille-3D (test)
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88.9
Accuracy
DarkNet53
80.58
82.74
84.9
87.06
Mar 31, 2020
Accuracy
mIoU
IoU (ground)
IoU (building)
IoU (pole)
IoU (bollard)
IoU (trash can)
IoU (barrier)
IoU (pedestrian)
IoU (vegetation)
Updated 1mo ago
Evaluation Results
Method
Method
Links
Accuracy
mIoU
IoU (ground)
IoU (building)
IoU (pole)
IoU (bollard)
IoU (trash can)
IoU (barrier)
IoU (pedestrian)
IoU (vegetation)
DarkNet53
2020.03
88.9
40
96.7
84.9
19.5
16.7
4.8
17.6
3.4
57.9
PolarNet
2020.03
87.5
43.7
96.8
69.1
32.2
27.6
2.4
27.5
12.1
51.6
SqueezeSegV2
2020.03
87.3
36.9
95.9
82.7
18.7
9.9
3.8
15.2
3.4
52.8
UNet
Projection=Cartesian BEV
2020.03
80.9
40.3
96
44
38.4
42.8
12.7
12.4
12.1
33.6
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