Method Details


Details for method 'GoogLeNetV1_ROB'

 

Method overview

name GoogLeNetV1_ROB
challenge pixel-level semantic labeling
details GoogLeNet-v1 FCN trained on Cityscapes, KITTI, and ScanNet, as required by the Robust Vision Challenge at CVPR'18 (http://robustvision.net/)
publication Anonymous
project page / code
used Cityscapes data fine annotations
used external data ImageNet, KITTI, ScanNet
runtime n/a
subsampling no
submission date April, 2018
previous submissions

 

Average results

Metric Value
IoU Classes 59.6107
iIoU Classes 35.1399
IoU Categories 83.0324
iIoU Categories 64.4251

 

Class results

Class IoU iIoU
road 96.6092 -
sidewalk 73.7704 -
building 87.1435 -
wall 27.116 -
fence 31.5918 -
pole 47.2207 -
traffic light 53.2359 -
traffic sign 59.0071 -
vegetation 89.6268 -
terrain 55.0949 -
sky 92.1503 -
person 72.3161 46.8655
rider 48.2823 27.2006
car 90.8773 83.4367
truck 29.773 16.1183
bus 40.0204 24.4205
train 33.8484 18.2762
motorcycle 42.9019 22.6491
bicycle 62.0171 42.1522

 

Category results

Category IoU iIoU
flat 97.3446 -
nature 88.4961 -
object 53.8987 -
sky 92.1503 -
construction 87.3971 -
human 73.5065 48.5833
vehicle 88.4336 80.2669

 

Links

Download results as .csv file

Benchmark page