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Semantic Segmentation On Isprs Potsdam

Metrics

Mean F1
Mean IoU
Overall Accuracy

Results

Performance results of various models on this benchmark

Model Name
Mean F1
Mean IoU
Overall Accuracy
Paper TitleRepository
AerialFormer-B94.189.193.9AerialFormer: Multi-resolution Transformer for Aerial Image Segmentation-
LSKNet-S93.187.292.0LSKNet: A Foundation Lightweight Backbone for Remote Sensing-
PSPNet (SAP)-74.388.56Stochastic Subsampling With Average Pooling-
ViT-B + RVSA-UperNet--90.77Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model-
EfficientUNets and Transformers93.7-91.8Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers-
BANet--91.06Transformer Meets Convolution: A Bilateral Awareness Network for Semantic Segmentation of Very Fine Resolution Urban Scene Images-
FT-UNetFormer93.387.592.0UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery-
RSP-Swin-T-UperNet--90.78An Empirical Study of Remote Sensing Pretraining-
MANet--91.318Multiattention 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--91.22Advancing Plain Vision Transformer Towards Remote Sensing Foundation Model-
ViT-G12X492.12-92.58A Billion-scale Foundation Model for Remote Sensing Images-
RSP-ResNet-50-UperNet--90.61An Empirical Study of Remote Sensing Pretraining-
RSP-ViTAEv2-S-UperNet--91.21An Empirical Study of Remote Sensing Pretraining-
ABCNet--91.3ABCNet: Attentive Bilateral Contextual Network for Efficient Semantic Segmentation of Fine-Resolution Remote Sensing Images-
IMP-ViTAEv2-S-UperNet--91.6An Empirical Study of Remote Sensing Pretraining-
UNetFormer92.886.891.3UNetFormer: 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-
SFA-Net93.5--SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation
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