Semantic Segmentation On Loveda
평가 지표
Category mIoU
평가 결과
이 벤치마크에서 각 모델의 성능 결과
비교 표
| 모델 이름 | Category mIoU |
|---|---|
| mtp-advancing-remote-sensing-foundation-model | 54.17 |
| decouplenet-a-lightweight-backbone-network | 53.1 |
| sfa-net-semantic-feature-adjustment-network | 54.9 |
| hi-resnet-a-high-resolution-remote-sensing | 52.6 |
| lwganet-a-lightweight-group-attention | 53.6 |
| large-selective-kernel-network-for-remote | 54.0 |
| aerialformer-multi-resolution-transformer-for | 54.1 |
| a-billion-scale-foundation-model-for-remote | 54.4 |
| loveda-a-remote-sensing-land-cover-dataset | 49.79 |
| u-net-ensemble-for-enhanced-semantic | 56.16 |
| advancing-plain-vision-transformer-towards | 51.95 |
| mtp-advancing-remote-sensing-foundation-model | 54.17 |
| large-selective-kernel-network-for-remote | 53.2 |
| mtp-advancing-remote-sensing-foundation-model | 52.39 |
| logcan-local-global-class-aware-network-for | 53.35 |
| scaling-efficient-masked-autoencoder-learning | 54.31 |
| advancing-plain-vision-transformer-towards | 52.44 |
| efficient-hybrid-transformer-learning-global | 52.40 |