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Few Shot Semantic Segmentation On Pascal 5I 5

Metrics

Mean IoU

Results

Performance results of various models on this benchmark

Paper TitleRepository
SegGPT (ViT)89.8SegGPT: Segmenting Everything In Context
GF-SAM82.6Bridge the Points: Graph-based Few-shot Segment Anything Semantically
PGMA-Net (ResNet-101)78.6Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond-
FPTrans (DeiT-B/16)78Feature-Proxy Transformer for Few-Shot Segmentation
DGPNet (ResNet-101)75.4Dense Gaussian Processes for Few-Shot Segmentation
PGMA-Net (ResNet-50)75.2Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond-
DCAMA (Swin-B)74.9Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation
PGMA-Net (ViT-B/16)74.6Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond-
AENet (ResNet-50)74.2Eliminating Feature Ambiguity for Few-Shot Segmentation
HMNet (ResNet-50)74.1Hybrid Mamba for Few-Shot Segmentation
MSANet (ResNet-101)73.99MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation
FPTrans (ViT-B/16)73.7Feature-Proxy Transformer for Few-Shot Segmentation
DGPNet (ResNet-50)73.5Dense Gaussian Processes for Few-Shot Segmentation
DACM (VAT, ResNet-101)73.3Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation
SSP (ResNet-101)73.1Self-Support Few-Shot Semantic Segmentation
MSANet (ResNet-50)72.6MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation
MSHNet72.3Multi-similarity based Hyperrelation Network for few-shot segmentation
BAM (SVF, ResNet-50)72.28Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning
VAT (ResNet-101)72Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation
MIANet (VGG-16)71.99MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation
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