Semantic Segmentation On Bjroad
Metriken
IoU
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Vergleichstabelle
| Modellname | IoU |
|---|---|
| aerial-images-meet-crowdsourced-trajectories | 62.85 |
| road-extraction-by-deep-residual-u-net | 54.24 |
| d-linknet-linknet-with-pretrained-encoder-and | 57.96 |
| bi-directional-cross-modality-feature | 62.14 |
| delivering-arbitrary-modal-semantic | 63.22 |
| cmx-cross-modal-fusion-for-rgb-x-semantic | 62.28 |
| deepdualmapper-a-gated-fusion-network-for | 60.19 |
| encoder-decoder-with-atrous-separable | 50.81 |
| linknet-exploiting-encoder-representations | 57.89 |
| u-net-convolutional-networks-for-biomedical | 54.88 |
| leveraging-crowdsourced-gps-data-for-road | 59.18 |