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Système

Few Shot Semantic Segmentation On Coco 20I

Métriques

Mean IoU

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle	Mean IoU	Paper Title	Repository
FPTrans (DeiT-B/16)	69.7	Feature-Proxy Transformer for Few-Shot Segmentation
HSNet (HM, ResNet-50)	65.2	HM: Hybrid Masking for Few-Shot Segmentation	-
DGPNet (ResNet-101)	70.1	Dense Gaussian Processes for Few-Shot Segmentation
HSNet (HM, ResNet-101)	66.5	HM: Hybrid Masking for Few-Shot Segmentation	-
MSDNet (ResNet-101)	73.9	MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping
VAT (HM, ResNet-50)	65.1	HM: Hybrid Masking for Few-Shot Segmentation	-
RPMM	49.6	Prototype Mixture Models for Few-shot Semantic Segmentation
CWT (ResNet-50)	59.5	Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer
RePRI (ResNet-50)	63.1	Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?
VAT + MSI (ResNet101)	69.2	MSI: Maximize Support-Set Information for Few-Shot Segmentation
DGPNet (ResNet-50)	68.9	Dense Gaussian Processes for Few-Shot Segmentation
MSDNet (ResNet-50)	72.1	MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping
FPTrans (ViT-B/16)	67.6	Feature-Proxy Transformer for Few-Shot Segmentation

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