Method Details
Details for method 'GALD-net'
Method overview
| name | GALD-net |
| challenge | pixel-level semantic labeling |
| details | We propose Global Aggregation then Local Distribution (GALD) scheme to distribute global information to each position adaptively according the local information surrounding the position. |
| publication | Global Aggregation then Local Distribution in Fully Convolutional Networks Xiangtai Li, Li Zhang, Ansheng You, Maoke Yang, Kuiyuan Yang, Yunhai Tong BMVC 2019 |
| project page / code | https://github.com/lxtGH/GALD_net |
| used Cityscapes data | fine annotations, coarse annotations |
| used external data | Mapillary |
| runtime | n/a |
| subsampling | no |
| submission date | February, 2019 |
| previous submissions |
Average results
| Metric | Value |
|---|---|
| IoU Classes | 83.1276 |
| iIoU Classes | 63.4849 |
| IoU Categories | 92.2452 |
| iIoU Categories | 81.4271 |
Class results
| Class | IoU | iIoU |
|---|---|---|
| road | 98.7948 | - |
| sidewalk | 87.5802 | - |
| building | 94.1835 | - |
| wall | 64.5675 | - |
| fence | 66.5406 | - |
| pole | 72.8465 | - |
| traffic light | 79.0412 | - |
| traffic sign | 82.217 | - |
| vegetation | 94.1592 | - |
| terrain | 73.0619 | - |
| sky | 96.0223 | - |
| person | 88.3038 | 72.8503 |
| rider | 75.2141 | 55.7875 |
| car | 96.4999 | 90.9287 |
| truck | 79.3227 | 51.198 |
| bus | 89.7172 | 58.5384 |
| train | 87.5446 | 58.7452 |
| motorcycle | 73.8065 | 52.5305 |
| bicycle | 80.0008 | 67.3003 |
Category results
| Category | IoU | iIoU |
|---|---|---|
| flat | 98.7853 | - |
| nature | 93.8186 | - |
| object | 78.0226 | - |
| sky | 96.0223 | - |
| construction | 94.4141 | - |
| human | 88.5138 | 73.7503 |
| vehicle | 96.1398 | 89.1039 |