Few Shot Semantic Segmentation On Coco 20I 1

评估指标

Mean IoU

评测结果

各个模型在此基准测试上的表现结果

		Paper Title	Repository
PGMA-Net (ResNet-101)	59.4	Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond	-
GF-SAM	58.7	Bridge the Points: Graph-based Few-shot Segment Anything Semantically
SegGPT (ViT)	56.1	SegGPT: Segmenting Everything In Context
PGMA-Net (ResNet-50)	54.3	Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond	-
Matcher(DINOv2)	52.7	Matcher: Segment Anything with One Shot Using All-Purpose Feature Matching
DiffewS (SD2.1)	52.2	Unleashing the Potential of the Diffusion Model in Few-shot Semantic Segmentation
HMNet (ResNet-50)	52.1	Hybrid Mamba for Few-Shot Segmentation
AENet (ResNet-50)	51.3	Eliminating Feature Ambiguity for Few-Shot Segmentation
DCAMA (Swin-B)	50.9	Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation
MSANet (ResNet-101)	50.45	MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation
HDMNet (ResNet-50)	50	Hierarchical Dense Correlation Distillation for Few-Shot Segmentation
VAT + MSI (ResNet-101)	49.8	MSI: Maximize Support-Set Information for Few-Shot Segmentation
HMNet (VGG-16)	49.1	Hybrid Mamba for Few-Shot Segmentation
MSDNet (ResNet-101)	48.5	MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping
BAM (SVF, ResNet-50)	48.47	Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
SCCAN (ResNet-101)	48.2	Self-Calibrated Cross Attention Network for Few-Shot Segmentation
PFENet (SVF, ResNet-50)	48.02	Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
MIANet (ResNet-50)	47.66	MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation
FPTrans (DeiT-B/16)	47	Feature-Proxy Transformer for Few-Shot Segmentation
ProtoFormer (ResNet-101)	47	Prototype as Query for Few Shot Semantic Segmentation

0 of 85 row(s) selected.