Open Vocabulary Semantic Segmentation On 7
Métriques
mIoU
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | mIoU |
|---|---|
| open-vocabulary-panoptic-segmentation-with | 10 |
| silc-improving-vision-language-pretraining | 25.8 |
| collaborative-vision-text-representation | 21.6 |
| learning-mask-aware-clip-representations-for | 15.7 |
| maskclip-a-mask-based-clip-fine-tuning | 23.9 |
| open-vocabulary-panoptic-segmentation-with-1 | 14.5 |
| sed-a-simple-encoder-decoder-for-open | 22.6 |
| open-vocabulary-semantic-segmentation-with-4 | 21.0 |
| mask-adapter-the-devil-is-in-the-masks-for | 22.7 |
| open-vocabulary-segmentation-with-semantic | 16.7 |
| cat-seg-cost-aggregation-for-open-vocabulary | 23.8 |
| convolutions-die-hard-open-vocabulary-1 | 18.2 |
| open-vocabulary-semantic-segmentation-with | 12.4 |