Method Details


Details for method 'SRC-B-MachineLearningLab'

 

Method overview

name SRC-B-MachineLearningLab
challenge pixel-level semantic labeling
details Samsung Research Center MachineLearningLab. The result is tested by multi scale and filp. The paper is in preparing.
publication Jianlong Yuan, Zelu Deng, Shu Wang, Zhenbo Luo
project page / code
used Cityscapes data fine annotations, coarse annotations
used external data ImageNet
runtime n/a
subsampling no
submission date August, 2018
previous submissions

 

Average results

Metric Value
IoU Classes 82.4876
iIoU Classes 60.6631
IoU Categories 91.8136
iIoU Categories 81.4875

 

Class results

Class IoU iIoU
road 98.7264 -
sidewalk 87.2914 -
building 94.0168 -
wall 64.8086 -
fence 64.4752 -
pole 70.7068 -
traffic light 76.7335 -
traffic sign 81.2206 -
vegetation 93.9585 -
terrain 73.8663 -
sky 95.8668 -
person 87.8758 72.8885
rider 72.6575 51.39
car 96.2573 91.0492
truck 79.2042 44.2228
bus 92.1619 57.027
train 88.1155 53.8644
motorcycle 71.5498 49.5469
bicycle 77.7714 65.3157

 

Category results

Category IoU iIoU
flat 98.7833 -
nature 93.6873 -
object 76.4173 -
sky 95.8668 -
construction 94.1364 -
human 87.8805 73.7331
vehicle 95.9233 89.242

 

Links

Download results as .csv file

Benchmark page