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SOTA
Semantische Segmentierung
Semantic Segmentation On Isprs Potsdam
Semantic Segmentation On Isprs Potsdam
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Mean F1
Mean IoU
Overall Accuracy
Ergebnisse
Leistungsergebnisse verschiedener Modelle zu diesem Benchmark
Columns
Modellname
Mean F1
Mean IoU
Overall Accuracy
Paper Title
Repository
AerialFormer-B
94.1
89.1
93.9
AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation
LSKNet-S
93.1
87.2
92.0
LSKNet: A Foundation Lightweight Backbone for Remote Sensing
PSPNet (SAP)
-
74.3
88.56
Stochastic Subsampling With Average Pooling
-
ViT-B + RVSA-UperNet
-
-
90.77
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
EfficientUNets and Transformers
93.7
-
91.8
Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers
-
BANet
-
-
91.06
Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images
FT-UNetFormer
93.3
87.5
92.0
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
RSP-Swin-T-UperNet
-
-
90.78
An Empirical Study of Remote Sensing Pretraining
MANet
-
-
91.318
Multiattention network for semantic segmentation of fine-resolution remote sensing images
-
U-Net (ConvFormer-M36)
-
89.45
-
U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery
-
ViTAE-B + RVSA -UperNet
-
-
91.22
Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
ViT-G12X4
92.12
-
92.58
A Billion-scale Foundation Model for Remote Sensing Images
-
RSP-ResNet-50-UperNet
-
-
90.61
An Empirical Study of Remote Sensing Pretraining
RSP-ViTAEv2-S-UperNet
-
-
91.21
An Empirical Study of Remote Sensing Pretraining
ABCNet
-
-
91.3
ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images
IMP-ViTAEv2-S-UperNet
-
-
91.6
An Empirical Study of Remote Sensing Pretraining
UNetFormer
92.8
86.8
91.3
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
DC-Swin
93.25
87.56
92.0
A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images
SFA-Net
93.5
-
-
SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation
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