Real Time Semantic Segmentation On Camvid
Metrics
mIoU
Results
Performance results of various models on this benchmark
Comparison Table
| Model Name | mIoU |
|---|---|
| efficient-dense-modules-of-asymmetric | 66.4 |
| pp-liteseg-a-superior-real-time-semantic | 75 |
| bisenet-v2-bilateral-network-with-guided | 72.4 |
| bisenet-v2-bilateral-network-with-guided | 78.5 |
| bisenet-v2-bilateral-network-with-guided | 73.2 |
| temporally-distributed-networks-for-fast | 72.6 |
| bisenet-v2-bilateral-network-with-guided | 76.7 |
| hyperseg-patch-wise-hypernetwork-for-real | 78.4 |
| pyramid-scene-parsing-network | - |
| s-textsuperscript-2-fpn-scale-ware-strip | 71.0 |
| pidnet-a-real-time-semantic-segmentation | 80.1 |
| multi-scale-context-aggregation-by-dilated | 65.3% |
| s-textsuperscript-2-fpn-scale-ware-strip | 74.2 |
| rtformer-efficient-design-for-real-time | 81.4 |
| semantic-image-segmentation-with-deep | 61.6% |
| bisenet-bilateral-segmentation-network-for | 68.7% |
| deep-dual-resolution-networks-for-real-time | 74.7 |
| icnet-for-real-time-semantic-segmentation-on | 67.1% |
| pp-liteseg-a-superior-real-time-semantic | 73.3 |
| segnet-a-deep-convolutional-encoder-decoder | 46.4% |
| rethink-dilated-convolution-for-real-time | 80.9 |
| temporally-distributed-networks-for-fast | 76.0 |
| pidnet-a-real-time-semantic-segmentation | 82.0 |
| s-textsuperscript-2-fpn-scale-ware-strip | 69.5 |
| mobile-seed-joint-semantic-segmentation-and | 73.6% |
| deep-dual-resolution-networks-for-real-time | 80.6 |
| hyperseg-patch-wise-hypernetwork-for-real | 79.1 |
| efficient-road-lane-marking-detection-with | 63.5 |