Unsupervised Domain Adaptation On Gtav To
المقاييس
mIoU
النتائج
نتائج أداء النماذج المختلفة على هذا المعيار القياسي
جدول المقارنة
اسم النموذج | mIoU |
---|---|
procst-boosting-semantic-segmentation-using | 69.4 |
bidirectional-self-training-with-multiple | 61.2 |
sepico-semantic-guided-pixel-contrast-for | 70.3 |
pipa-pixel-and-patch-wise-self-supervised | 75.6 |
smoothing-matters-momentum-transformer-for | 63.9 |
context-aware-mixup-for-domain-adaptive | 55.2 |
dual-level-interaction-for-domain-adaptive | 71.0 |
bimal-bijective-maximum-likelihood-approach | 47.3 |
daformer-improving-network-architectures-and | 68.3 |
rectifying-pseudo-label-learning-via | 50.3 |
pipa-pixel-and-patch-wise-self-supervised | 71.7 |
context-aware-mixup-for-domain-adaptive | 70.0 |
unsupervised-scene-adaptation-with-memory | 45.5 |
g2l-a-global-to-local-alignment-method-for | 59.7 |
a-novel-unsupervised-domain-adaption-method | 58.8 |
mic-masked-image-consistency-for-context | 75.9 |
adaptive-boosting-for-domain-adaptation | 50.9 |
rethinking-ensemble-distillation-for-semantic | 57.98 |
hrda-context-aware-high-resolution-domain | 73.8 |
cluda-contrastive-learning-in-unsupervised | 74.4 |