HyperAI
Home
News
Latest Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
English
HyperAI
Toggle sidebar
Search the site…
⌘
K
Home
SOTA
Semantic Segmentation
Semantic Segmentation On Isprs Vaihingen
Semantic Segmentation On Isprs Vaihingen
Metrics
Average F1
Overall Accuracy
Results
Performance results of various models on this benchmark
Columns
Model Name
Average F1
Overall Accuracy
Paper Title
Repository
EfficientUNets and Transformers
93.7
91.8
Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers
-
UNetFormer
90.4
91.0
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
ABCNet
-
90.7
ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images
LSKNet-T
91.7
93.6
LSKNet: A Foundation Lightweight Backbone for Remote Sensing
BANet
-
90.5
Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images
SFA-Net
91.2
-
SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation
LSKNet-S
91.8
93.6
LSKNet: A Foundation Lightweight Backbone for Remote Sensing
DC-Swin
90.7
91.6
A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images
FT-UNetFormer
91.3
91.6
UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
UPerNet (SAP)
-
90.14
Stochastic Subsampling With Average Pooling
-
MANet
-
90.963
Multiattention network for semantic segmentation of fine-resolution remote sensing images
-
0 of 11 row(s) selected.
Previous
Next