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Système

Semantic Segmentation On Bjroad

Métriques

IoU

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	IoU	Paper Title	Repository
CMMPNe	62.85	Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction	-
Res-UNet	54.24	Road Extraction by Deep Residual U-Net
D-LinkNet	57.96	D-LinkNet: LinkNet with Pretrained Encoder and Dilated Convolution for High Resolution Satellite Imagery Road Extraction
SA-Gate	62.14	Bi-directional Cross-Modality Feature Propagation with Separation-and-Aggregation Gate for RGB-D Semantic Segmentation
CMNeXt	63.22	Delivering Arbitrary-Modal Semantic Segmentation
CMX	62.28	CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
DeepDualMapper	60.19	DeepDualMapper: A Gated Fusion Network for Automatic Map Extraction using Aerial Images and Trajectories	-
DeepLabv3+	50.81	Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
LinkNet	57.89	LinkNet: Exploiting Encoder Representations for Efficient Semantic Segmentation
UNet	54.88	U-Net: Convolutional Networks for Biomedical Image Segmentation
Sun et al.	59.18	Leveraging Crowdsourced GPS Data for Road Extraction from Aerial Imagery	-

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