semantic-8 results

We use Intersection over Union (IoU) and Overall Accuracy (OA) as metrics. For more details hover the curser over the symbols or click on a classifier. In order to sort the results differently click on a symbol.

NameA_IoUOA[s]IoU 1IoU 2IoU 3IoU 4IoU 5IoU 6IoU 7IoU 8
1SnapNet0.6740.9100.000.8960.7950.7480.5610.9090.3650.3430.772
Unstructured point cloud semantic labeling using deep segmentation networks. A. Boulch, B. Le Saux and N. Audebert, Eurographics 3DOR 2017
2HarrisNet0.6230.8810.000.8180.7370.7420.6250.9270.2830.1780.671
Anonymous submission
3FCNVoxNet0.3720.523138929.000.0660.2720.5800.3640.8090.2830.0950.509
Anonymous submission
4TMLC-MS0.4940.85038421.000.9110.6950.3280.2160.8760.2590.1130.553
Timo Hackel, Jan D. Wegner, Konrad Schindler: Fast semantic segmentation of 3d point clouds with strongly varying density. ISPRS Annals - ISPRS Congress, Prague, 2016
5TML-PC0.3910.7450.000.8040.6610.4230.4120.6470.1240.0000.058
Mind the gap: modeling local and global context in (road) networks: Javier Montoya, Jan D. Wegner, Lubor Ladicky, Konrad Schindler. In: German Conference on Pattern Recognition (GCPR), M√ľnster, Germany, 2014