Method Details
Details for method 'Bilateral_attention_semantic'
Method overview
| name | Bilateral_attention_semantic |
| challenge | pixel-level semantic labeling |
| details | use ASSP、DCN、Depth to space model for semantic segmentation Previously listed in the benchmark table as: BiseAsspDcnDts-v1 |
| publication | Anonymous |
| project page / code | |
| used Cityscapes data | fine annotations |
| used external data | |
| runtime | 0.0128 s NVIDIA Tesla V100 32GB |
| subsampling | no |
| submission date | September, 2020 |
| previous submissions |
Average results
| Metric | Value |
|---|---|
| IoU Classes | 74.8585 |
| iIoU Classes | 53.491 |
| IoU Categories | 90.1755 |
| iIoU Categories | 78.6611 |
Class results
| Class | IoU | iIoU |
|---|---|---|
| road | 98.4404 | - |
| sidewalk | 85.0725 | - |
| building | 92.3015 | - |
| wall | 48.4282 | - |
| fence | 55.3905 | - |
| pole | 65.0352 | - |
| traffic light | 73.975 | - |
| traffic sign | 76.1325 | - |
| vegetation | 93.2731 | - |
| terrain | 71.232 | - |
| sky | 94.9386 | - |
| person | 85.3081 | 68.4646 |
| rider | 67.295 | 45.6909 |
| car | 95.4474 | 89.3784 |
| truck | 57.8666 | 30.7824 |
| bus | 67.5854 | 49.1795 |
| train | 58.8216 | 41.4946 |
| motorcycle | 61.3478 | 40.6074 |
| bicycle | 74.4195 | 62.3303 |
Category results
| Category | IoU | iIoU |
|---|---|---|
| flat | 98.6433 | - |
| nature | 92.9725 | - |
| object | 71.2619 | - |
| sky | 94.9386 | - |
| construction | 92.7825 | - |
| human | 85.792 | 69.8502 |
| vehicle | 94.8376 | 87.4721 |