HyperAIHyperAI

Few Shot Semantic Segmentation On Pascal 5I 5

المقاييس

Mean IoU

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج
Mean IoU
Paper TitleRepository
HDMNet (ResNet-50)71.8Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-
APANet (VGG-16)62.6APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation-
PFENet (SVF, VGG-16)69.8Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning-
MSHNet72.3Multi-similarity based Hyperrelation Network for few-shot segmentation-
FECANet (VGG-16)66.7FECANet: Boosting Few-Shot Semantic Segmentation with Feature-Enhanced Context-Aware Network-
ASGNet (ResNet-101)64.36Adaptive Prototype Learning and Allocation for Few-Shot Segmentation-
PFENet (ResNet-101)61.4Prior Guided Feature Enrichment Network for Few-Shot Segmentation-
MSDNet (ResNet-50)68.7MSDNet: Multi-Scale Decoder for Few-Shot Semantic Segmentation via Transformer-Guided Prototyping-
PANet (VGG-16)55.7PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment-
DCAMA (ResNet-50)68.5Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation-
DACM (VAT, ResNet-50)71.7Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation-
SSP (ResNet-101)73.1Self-Support Few-Shot Semantic Segmentation-
MIANet (ResNet-50)71.59MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation-
SCCAN (ResNet-101)71.5Self-Calibrated Cross Attention Network for Few-Shot Segmentation-
RePRI (ResNet-50)66.6Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?-
MSANet (ResNet-101)73.99MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation-
MLC (ResNet-50)66.8Mining Latent Classes for Few-shot Segmentation-
PFENet (SCL, ResNet-50)62.9Self-Guided and Cross-Guided Learning for Few-Shot Segmentation-
PGNet (ResNet-50)58.5Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation-
MCE (ResNet-50)70.03Masked Cross-image Encoding for Few-shot Segmentation-
0 of 96 row(s) selected.