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Semantic Segmentation On Potsdam

평가 지표

mIoU

평가 결과

이 벤치마크에서 각 모델의 성능 결과

		Paper Title
LMFNet-3	86.39	LMFNet: An Efficient Multimodal Fusion Approach for Semantic Segmentation in High-Resolution Remote Sensing
CMX	85.97	CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
LMFNet-2	85.51	LMFNet: An Efficient Multimodal Fusion Approach for Semantic Segmentation in High-Resolution Remote Sensing
UnetFormer	85.18	UNetFormer: A UNet-like Transformer for Efficient Semantic Segmentation of Remote Sensing Urban Scene Imagery
SegFormer-B2	84.65	SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
SegFormer-B1	84.37	SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
V-FuseNet	84.36	Beyond RGB: Very High Resolution Urban Remote Sensing With Multimodal Deep Networks
SA-Gate	84.28	Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
SegFormer-B0	83.67	SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
FPN	82.99	Feature Pyramid Networks for Object Detection
PSPNet	82.98	Pyramid Scene Parsing Network

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Semantic Segmentation On Potsdam | SOTA | HyperAI초신경