Startseite Neuigkeiten Neueste Forschungsarbeiten Tutorials Datensätze Wiki SOTA LLM-Modelle GPU-Rangliste Veranstaltungen

Deutsch

Semantic Segmentation On Potsdam

Metriken

mIoU

Ergebnisse

Leistungsergebnisse verschiedener Modelle zu diesem Benchmark

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

0 of 11 row(s) selected.

Semantic Segmentation On Potsdam | SOTA | HyperAI