Method Details
Details for method 'Fast-SCNN (Half-resolution)'
Method overview
| name | Fast-SCNN (Half-resolution) |
| challenge | pixel-level semantic labeling |
| details | The encoder-decoder framework is state-of-the-art for offline semantic image segmentation. Since the rise in autonomous systems, real-time computation is increasingly desirable. In this paper, we introduce fast segmentation convolutional neural network (Fast-SCNN), an above real-time semantic segmentation model on high resolution image data (1024x2048px) suited to efficient computation on embedded devices with low memory. Building on existing two-branch methods for fast segmentation, we introduce our `learning to downsample' module which computes low-level features for multiple resolution branches simultaneously. Our network combines spatial detail at high resolution with deep features extracted at lower resolution, yielding an accuracy of 68.0% mean intersection over union at 123.5 frames per second on Cityscapes. We also show that large scale pre-training is unnecessary. We thoroughly validate our metric in experiments with ImageNet pre-training and the coarse labeled data of Cityscapes. Finally, we show even faster computation with competitive results on subsampled inputs, without any network modifications. |
| publication | Fast-SCNN: Fast Semantic Segmentation Network Rudra P K Poudel, Stephan Liwicki, Roberto Cipolla https://arxiv.org/abs/1902.04502 |
| project page / code | |
| used Cityscapes data | fine annotations, coarse annotations |
| used external data | |
| runtime | 0.0035 s Nvidia Titan Xp (Pascal) |
| subsampling | 2 |
| submission date | November, 2018 |
| previous submissions |
Average results
| Metric | Value |
|---|---|
| IoU Classes | 62.8271 |
| iIoU Classes | 31.9036 |
| IoU Categories | 80.5114 |
| iIoU Categories | 57.1292 |
Class results
| Class | IoU | iIoU |
|---|---|---|
| road | 97.393 | - |
| sidewalk | 77.7933 | - |
| building | 87.4057 | - |
| wall | 39.6781 | - |
| fence | 41.7532 | - |
| pole | 34.9656 | - |
| traffic light | 39.3722 | - |
| traffic sign | 50.4882 | - |
| vegetation | 88.506 | - |
| terrain | 63.3335 | - |
| sky | 92.6937 | - |
| person | 65.7443 | 36.7483 |
| rider | 46.3646 | 17.1671 |
| car | 91.0099 | 79.6037 |
| truck | 56.8599 | 16.755 |
| bus | 70.3143 | 27.0025 |
| train | 56.5166 | 29.919 |
| motorcycle | 40.8937 | 14.9045 |
| bicycle | 52.6286 | 33.1285 |
Category results
| Category | IoU | iIoU |
|---|---|---|
| flat | 97.6796 | - |
| nature | 88.0269 | - |
| object | 42.5333 | - |
| sky | 92.6937 | - |
| construction | 87.3266 | - |
| human | 65.893 | 37.6338 |
| vehicle | 89.4264 | 76.6246 |