Method Details
Details for method 'SERNet-Former Partial Result (Munich 250-end)'
Method overview
| name | SERNet-Former Partial Result (Munich 250-end) |
| challenge | pixel-level semantic labeling |
| details | The test results of SERNet-Former could only be acquired partially as this result shows the accuracy of the network on partially tested dataset ranging from Munich's 250th sample to the end. |
| publication | SERNet-Former: Semantic Segmentation by Efficient Residual Network with Attention-Boosting Gates and Attention-Fusion Networks Serdar Erisen https://doi.org/10.48550/arXiv.2401.15741 |
| project page / code | https://github.com/serdarch/SERNet-Former |
| used Cityscapes data | fine annotations |
| used external data | ImageNet |
| runtime | n/a |
| subsampling | no |
| submission date | January, 2024 |
| previous submissions |
Average results
| Metric | Value |
|---|---|
| IoU Classes | 16.8402 |
| iIoU Classes | 11.825 |
| IoU Categories | 17.1933 |
| iIoU Categories | 13.2974 |
Class results
| Class | IoU | iIoU |
|---|---|---|
| road | 16.0035 | - |
| sidewalk | 11.9402 | - |
| building | 14.1089 | - |
| wall | 6.94112 | - |
| fence | 9.32168 | - |
| pole | 11.3617 | - |
| traffic light | 17.7608 | - |
| traffic sign | 16.1071 | - |
| vegetation | 16.3733 | - |
| terrain | 20.436 | - |
| sky | 14.7695 | - |
| person | 28.0071 | 14.1022 |
| rider | 14.2157 | 9.62846 |
| car | 17.4336 | 11.6353 |
| truck | 19.7195 | 10.8358 |
| bus | 25.3284 | 13.4508 |
| train | 27.5322 | 16.6474 |
| motorcycle | 13.0573 | 7.27801 |
| bicycle | 19.5456 | 11.0216 |
Category results
| Category | IoU | iIoU |
|---|---|---|
| flat | 15.7665 | - |
| nature | 16.7766 | - |
| object | 13.9349 | - |
| sky | 14.7695 | - |
| construction | 13.9745 | - |
| human | 26.8043 | 14.3483 |
| vehicle | 18.3269 | 12.2465 |