Details for method 'MaskRCNN_BOSH'
Method overview
| name |
MaskRCNN_BOSH |
| challenge |
pixel-level semantic labeling |
| details |
MaskRCNN segmentation baseline for Bosh autodrive challenge , using Matterport's implementation of Mask RCNN https://github.com/matterport/Mask_RCNN 55k iterations, default parameters (backbone :resenet 101)
each pixel is assigend with label-id based on its highest class score |
| publication |
Jin shengtao, Yi zhihao, Liu wei [Our team name is firefly]
|
| project page / code |
|
| used Cityscapes data |
fine annotations |
| used external data |
coco |
| runtime |
n/a |
| subsampling |
no |
| submission date |
June, 2018 |
| previous submissions |
|
Average results
| Metric |
Value |
| IoU Classes | 41.5943 |
| iIoU Classes | 19.2986 |
| IoU Categories | 61.2908 |
| iIoU Categories | 31.2781 |
Class results
| Class |
IoU |
iIoU |
| road | 84.0654 | - |
| sidewalk | 20.6033 | - |
| building | 68.753 | - |
| wall | 15.8263 | - |
| fence | 12.5805 | - |
| pole | 11.1466 | - |
| traffic light | 33.7419 | - |
| traffic sign | 40.7674 | - |
| vegetation | 65.3318 | - |
| terrain | 7.45913 | - |
| sky | 50.8492 | - |
| person | 60.2306 | 24.1512 |
| rider | 38.5047 | 16.6114 |
| car | 81.7904 | 41.0207 |
| truck | 32.8656 | 11.2989 |
| bus | 44.5179 | 17.4347 |
| train | 58.5633 | 20.3863 |
| motorcycle | 28.8212 | 9.36296 |
| bicycle | 33.8738 | 14.1224 |
Category results
| Category |
IoU |
iIoU |
| flat | 90.4843 | - |
| nature | 61.949 | - |
| object | 22.2331 | - |
| sky | 50.8492 | - |
| construction | 68.2131 | - |
| human | 58.2264 | 24.1195 |
| vehicle | 77.0807 | 38.4368 |
Links
Download results as .csv file
Benchmark page
