Image Segmentation
Transformers
PyTorch
upernet
Inference Endpoints
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# Fast-SCNN for Semantic Segmentation

## Introduction

[ALGORITHM]

```latex
@article{poudel2019fast,
  title={Fast-scnn: Fast semantic segmentation network},
  author={Poudel, Rudra PK and Liwicki, Stephan and Cipolla, Roberto},
  journal={arXiv preprint arXiv:1902.04502},
  year={2019}
}
```

## Results and models

### Cityscapes

|   Method   | Backbone  | Crop Size | Lr schd | Mem (GB) | Inf time (fps) | mIoU  | mIoU(ms+flip) |                                                                                                                                                                                              download                                                                                              |
|------------|-----------|-----------|--------:|----------|----------------|------:|---------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| Fast-SCNN  | Fast-SCNN | 512x1024  |   80000 |      8.4 |          63.61 | 69.06 | -             | [model](https://download.openmmlab.com/mmsegmentation/v0.5/fast_scnn/fast_scnn_4x8_80k_lr0.12_cityscapes-f5096c79.pth) | [log](https://download.openmmlab.com/mmsegmentation/v0.5/fast_scnn/fast_scnn_4x8_80k_lr0.12_cityscapes-20200807_165744.log.json)     |