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Semantic Segmentation On Isprs Potsdam

Métriques

Mean F1
Mean IoU
Overall Accuracy

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
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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Semantic Segmentation On Isprs Potsdam | SOTA | HyperAI