Open Vocabulary Semantic Segmentation On 2
评估指标
mIoU
评测结果
各个模型在此基准测试上的表现结果
比较表格
模型名称 | mIoU |
---|---|
ttd-text-tag-self-distillation-enhancing | 12.7 |
learning-mask-aware-clip-representations-for | 32.0 |
convolutions-die-hard-open-vocabulary-1 | 34.1 |
collaborative-vision-text-representation | 36.1 |
cat-seg-cost-aggregation-for-open-vocabulary | 37.9 |
opendas-domain-adaptation-for-open-vocabulary | 35.8 |
2112-14757 | 20.5 |
open-vocabulary-segmentation-with-semantic | 33.5 |
mask-adapter-the-devil-is-in-the-masks-for | 38.2 |
open-vocabulary-panoptic-segmentation-with | 23.7 |
模型 11 | 20.7 |
open-vocabulary-semantic-segmentation-with-4 | 32.8 |
ttd-text-tag-self-distillation-enhancing | 17.0 |
open-vocabulary-panoptic-segmentation-with-1 | 29.9 |
open-vocabulary-semantic-segmentation-with-2 | 31.4 |
silc-improving-vision-language-pretraining | 37.7 |
open-vocabulary-semantic-segmentation-with | 29.6 |
in-defense-of-lazy-visual-grounding-for-open | 15.8 |
maskclip-a-mask-based-clip-fine-tuning | 38.2 |
clipself-vision-transformer-distills-itself | 34.5 |
sed-a-simple-encoder-decoder-for-open | 35.2 |