SOTAVerified

Few-Shot Semantic Segmentation

Few-shot semantic segmentation (FSS) learns to segment target objects in query image given few pixel-wise annotated support image.

Papers

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Showing 126–150 of 168 papers

TitleStatusHype
Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations—0
Few-Shot Semantic Segmentation with Democratic Attention Networks—0
Few-Shot Semantic Segmentation With Cyclic Memory Network—0
Few-shot Semantic Segmentation with Support-induced Graph Convolutional Network—0
FGNet: Towards Filling the Intra-class and Inter-class Gaps for Few-shot Segmentation—0
ForamViT-GAN: Exploring New Paradigms in Deep Learning for Micropaleontological Image Analysis—0
Generalized Few-Shot Semantic Segmentation: All You Need is Fine-Tuning—0
Generative Model-Based Fusion for Improved Few-Shot Semantic Segmentation of Infrared Images—0
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-Extended Abstract—0
Hypercorrelation Squeeze for Few-Shot Segmenation—0
Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation—0
Interclass Prototype Relation for Few-Shot Segmentation—0
Is Foreground Prototype Sufficient? Few-Shot Medical Image Segmentation with Background-Fused Prototype—0
Language-guided Few-shot Semantic Segmentation—0
LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation—0
Localization and Expansion: A Decoupled Framework for Point Cloud Few-shot Semantic Segmentation—0
Masked Cross-image Encoding for Few-shot Segmentation—0
Memory-guided Network with Uncertainty-based Feature Augmentation for Few-shot Semantic Segmentation—0
Meta-Learning via Learning with Distributed Memory—0
MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning—0
Organizing Background to Explore Latent Classes for Incremental Few-shot Semantic Segmentation—0
Overcoming Support Dilution for Robust Few-shot Semantic Segmentation—0
PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning—0
Prediction Calibration for Generalized Few-shot Semantic Segmentation—0
Progressively Dual Prior Guided Few-shot Semantic Segmentation—0
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All datasetsPASCAL-5i (1-Shot)PASCAL-5i (5-Shot)COCO-20i (1-shot)COCO-20i (5-shot)FSS-1000 (1-shot)FSS-1000 (5-shot)COCO-20i -> Pascal VOC (1-shot)COCO-20i -> Pascal VOC (5-shot)COCO-20i (2-way 1-shot)COCO-20i (10-shot)PASCAL-5i (10-Shot)FSS-1000

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SegGPT (ViT)Mean IoU83.2—Unverified
2DCAMA (ResNet-101)FB-IoU77.6—Unverified
3PGMA-Net (ResNet-101)Mean IoU77.6—Unverified
4PGMA-Net (ResNet-50)Mean IoU74.1—Unverified
5PGMA-Net (ViT-B/16)Mean IoU74.1—Unverified
6GF-SAM (DINOv2)Mean IoU72.1—Unverified
7HMNet (ResNet-50)Mean IoU70.4—Unverified
8AENet (ResNet-50)Mean IoU70.3—Unverified
9HDMNet (DifFSS, ResNet-50)Mean IoU70.2—Unverified
10VAT + MSI (ResNet-101)Mean IoU70.1—Unverified
#ModelMetricClaimedVerifiedStatus
1SegGPT (ViT)Mean IoU89.8—Unverified
2GF-SAM (DINOv2)Mean IoU82.6—Unverified
3PGMA-Net (ResNet-101)Mean IoU78.6—Unverified
4FPTrans (DeiT-B/16)Mean IoU78—Unverified
5DGPNet (ResNet-101)Mean IoU75.4—Unverified
6PGMA-Net (ResNet-50)Mean IoU75.2—Unverified
7DCAMA (Swin-B)Mean IoU74.9—Unverified
8PGMA-Net (ViT-B/16)Mean IoU74.6—Unverified
9AENet (ResNet-50)Mean IoU74.2—Unverified
10HMNet (ResNet-50)Mean IoU74.1—Unverified