Method Details


Details for method 'ERFNet (from scratch)'

 

Method overview

name ERFNet (from scratch)
challenge pixel-level semantic labeling
details ERFNet trained from scratch only on the fine train (2975) annotated images
publication Anonymous
project page / code
used Cityscapes data fine annotations
used external data
runtime 0.02 s
1 Titan X (Maxwell)
subsampling 2
submission date January, 2017
previous submissions

 

Average results

Metric Value
IoU Classes 67.3146
iIoU Classes 42.9913
IoU Categories 85.9597
iIoU Categories 71.7346

 

Class results

Class IoU iIoU
road 97.3908 -
sidewalk 79.6208 -
building 89.6563 -
wall 45.2995 -
fence 46.144 -
pole 55.1636 -
traffic light 61.2134 -
traffic sign 65.7921 -
vegetation 91.3026 -
terrain 68.5179 -
sky 93.5926 -
person 75.7618 58.541
rider 58.1249 33.9241
car 92.6665 85.0431
truck 46.0601 23.5801
bus 56.7429 35.4155
train 45.5143 29.5465
motorcycle 49.0455 30.1592
bicycle 61.3676 47.7211

 

Category results

Category IoU iIoU
flat 98.0269 -
nature 90.9303 -
object 61.741 -
sky 93.5926 -
construction 89.6734 -
human 76.4579 59.9839
vehicle 91.2955 83.4852

 

Links

Download results as .csv file

Benchmark page