Semantic Segmentation On Selma

mIoU

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	mIoU	Paper Title
PSPNet	68.4	Pyramid Scene Parsing Network
SegFormer	77.2	SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
DeepLabV2	68.9	DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
CMX	91.7	CMX: Cross-Modal Fusion for RGB-X Semantic Segmentation with Transformers
DeepLabV3	70.7	Rethinking Atrous Convolution for Semantic Image Segmentation
UNet	36.2	U-Net: Convolutional Networks for Biomedical Image Segmentation
FCN	68.2	Fully Convolutional Networks for Semantic Segmentation

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