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Semantic Segmentation On Isprs Potsdam

评估指标

Mean F1
Mean IoU
Overall Accuracy

评测结果

各个模型在此基准测试上的表现结果

Paper TitleRepository
AerialFormer-B94.189.193.9AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation
ViT-G12X492.12-92.58A Billion-scale Foundation Model for Remote Sensing Images-
LSKNet-S93.187.292.0LSKNet: A Foundation Lightweight Backbone for Remote Sensing
FT-UNetFormer93.387.592.0UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
DC-Swin93.2587.5692.0A Novel Transformer Based Semantic Segmentation Scheme for Fine-Resolution Remote Sensing Images
EfficientUNets and Transformers93.7-91.8Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers-
IMP-ViTAEv2-S-UperNet--91.6An Empirical Study of Remote Sensing Pretraining
MANet--91.318Multiattention network for semantic segmentation of fine-resolution remote sensing images-
ABCNet--91.3ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images
UNetFormer92.886.891.3UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
ViTAE-B + RVSA -UperNet--91.22Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
RSP-ViTAEv2-S-UperNet--91.21An Empirical Study of Remote Sensing Pretraining
BANet--91.06Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images
RSP-Swin-T-UperNet--90.78An Empirical Study of Remote Sensing Pretraining
ViT-B + RVSA-UperNet--90.77Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model
RSP-ResNet-50-UperNet--90.61An Empirical Study of Remote Sensing Pretraining
PSPNet (SAP)-74.388.56Stochastic Subsampling With Average Pooling-
U-Net (ConvFormer-M36)-89.45-U-Net Ensemble for Enhanced Semantic Segmentation in Remote Sensing Imagery-
SFA-Net93.5--SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation-
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Semantic Segmentation On Isprs Potsdam | SOTA | HyperAI超神经