Facade Semantic Segmentation Benchmark
ZAHA
We observe that albeit deep-learning-driven methods achieve high performance on various tasks, the facade semantic segmentation still poses an unresolved challenge.
See the ZAHA WACV’25 paper introducing the challenge. Would you like to try and solve it? Please grab the data and report your results!
Facade Semantic Segmentation at LoFG3
LoFG stands for Level of Facade Generalization. See more in the ZAHA paper introducing the concept.
PointNet | PointNet++ | Point Transformer | DGCNN | |
---|---|---|---|---|
OA | 59.9 | 66.4 | 75.0 | 71.1 |
P | 46.1 | 37.8 | 52.7 | 53.6 |
R | 42.2 | 35.9 | 54.7 | 45.8 |
F1 | 38.7 | 34.8 | 52.1 | 44.5 |
IoU | 26.4 | 25.6 | 41.6 | 33.4 |
Class scores | ||||
wall | 61.1 | 68.5 | 76.8 | 83.8 |
window | 25.6 | 26.3 | 43.1 | 64.1 |
door | 13.5 | 7.8 | 19.8 | 21.6 |
balcony | 25.1 | 0.0 | 77.5 | 66.7 |
molding | 22.5 | 43.4 | 58.0 | 57.5 |
deco | 0.0 | 0.0 | 5.0 | 0.0 |
column | 22.4 | 33.4 | 0.0 | 37.2 |
arch | 19.2 | 25.4 | 50.2 | 2.6 |
stairs | 16.0 | 0.0 | 7.5 | 5.6 |
ground surface | 12.0 | 0.0 | 24.4 | 21.3 |
terrain | 53.5 | 53.5 | 57.6 | 68.0 |
roof | 18.7 | 6.8 | 66.3 | 57.4 |
blinds | 4.6 | 2.3 | 18.5 | 20.0 |
interior | 59.7 | 69.1 | 72.8 | 88.0 |
other | 42.7 | 47.1 | 70.6 | 74.1 |
Facade Semantic Segmentation at LoFG2
LoFG stands for Level of Facade Generalization. See more in the ZAHA paper introducing the concept.
PointNet | PointNet++ | Point Transformer | DGCNN | |
---|---|---|---|---|
OA | 71.9 | 75.5 | 78.2 | 82.6 |
P | 69.6 | 73.0 | 75.8 | 80.0 |
R | 68.1 | 73.0 | 76.6 | 81.8 |
F1 | 68.1 | 72.6 | 76.1 | 80.4 |
IoU | 55.8 | 59.8 | 63.9 | 68.5 |
Class scores | ||||
floor | 92.3 | 87.6 | 90.7 | 92.1 |
decoration | 26.2 | 47.1 | 47.0 | 70.0 |
structural | 60.9 | 65.5 | 67.0 | 85.2 |
opening | 28.2 | 27.2 | 36.0 | 66.2 |
other el. | 71.2 | 71.6 | 78.9 | 88.8 |