Method Details


Details for method 'EdgeSenseSeg'

 

Method overview

name EdgeSenseSeg
challenge pixel-level semantic labeling
details Deep segmentation network with hard negative mining and other tricks.
publication Anonymous
project page / code
used Cityscapes data fine annotations
used external data
runtime n/a
subsampling no
submission date October, 2017
previous submissions

 

Average results

Metric Value
IoU Classes 76.7648
iIoU Classes 57.1459
IoU Categories 89.7833
iIoU Categories 78.4579

 

Class results

Class IoU iIoU
road 98.3857 -
sidewalk 84.7894 -
building 92.454 -
wall 51.9914 -
fence 58.1482 -
pole 61.483 -
traffic light 72.9611 -
traffic sign 76.0664 -
vegetation 93.2508 -
terrain 71.8155 -
sky 95.0447 -
person 85.2392 68.3589
rider 68.5316 49.119
car 95.3796 88.8405
truck 62.3966 41.7955
bus 77.5506 53.1845
train 70.6995 46.861
motorcycle 66.8293 46.672
bicycle 75.5153 62.3355

 

Category results

Category IoU iIoU
flat 98.5929 -
nature 92.8865 -
object 68.9191 -
sky 95.0447 -
construction 92.9248 -
human 85.5948 69.6591
vehicle 94.5205 87.2567

 

Links

Download results as .csv file

Benchmark page