Few Shot Semantic Segmentation On Coco 20I 1

평가 지표

Mean IoU

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	Mean IoU	Paper Title	Repository
QCLNet (ResNet-50)	42.3	Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation
FPTrans (DeiT-B/16)	47	Feature-Proxy Transformer for Few-Shot Segmentation
IPMT (ResNet-101)	42.6	Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation
PANet (VGG-16)	20.9	PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment	-
FPTrans (ViT-B/16)	42	Feature-Proxy Transformer for Few-Shot Segmentation
MSANet (ResNet-50)	46.44	MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation
IPMT (ResNet-50)	43	Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation
MLC (ResNet-101)	37.5	Mining Latent Classes for Few-shot Segmentation
ASGNet (ResNet-50)	34.56	Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
BAM (SVF, VGG-16)	43.76	Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
BAM (DifFSS, ResNet-50)	43.6	DifFSS: Diffusion Model for Few-Shot Semantic Segmentation
APANet (ResNet-101)	41.9	APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation	-
SSP (ResNet-101)	42	Self-Support Few-Shot Semantic Segmentation
Matcher(DINOv2)	52.7	Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
QCLNet (ResNet-101)	43.6	Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation
AENet (VGG-16)	46.4	Eliminating Feature Ambiguity for Few-Shot Segmentation
ASNet (HM, ResNet-50)	44.7	HM: Hybrid Masking for Few-Shot Segmentation	-
MLC (ResNet-50)	35.1	Mining Latent Classes for Few-shot Segmentation
MSDNet (ResNet-101)	48.5	MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping
ProtoFormer (ResNet-50)	45.7	Prototype as Query for Few Shot Semantic Segmentation

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