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

Showing 101150 of 168 papers

TitleStatusHype
Texture based Prototypical Network for Few-Shot Semantic Segmentation of Forest Cover: Generalizing for Different Geographical Regions0
Integrative Few-Shot Learning for Classification and SegmentationCode1
Cross-Domain Few-Shot Semantic SegmentationCode1
HM: Hybrid Masking for Few-Shot SegmentationCode0
Multi-similarity based Hyperrelation Network for few-shot segmentationCode1
Learning What Not to Segment: A New Perspective on Few-Shot SegmentationCode2
Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With SupervoxelsCode1
Few-shot semantic segmentation via mask aggregationCode0
Language-driven Semantic SegmentationCode2
Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer0
Cost Aggregation Is All You Need for Few-Shot SegmentationCode1
Generalized Few-Shot Semantic Segmentation: All You Need is Fine-Tuning0
Meta-Learning via Learning with Distributed Memory0
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation0
Dual Prototypical Contrastive Learning for Few-shot Semantic SegmentationCode0
A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation0
MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning0
MaskSplit: Self-supervised Meta-learning for Few-shot Semantic SegmentationCode1
Pixel-by-Pixel Cross-Domain Alignment for Few-Shot Semantic SegmentationCode1
Few-shot Semantic Segmentation with Self-supervision from Pseudo-classesCode0
Dense Gaussian Processes for Few-Shot SegmentationCode1
PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior MaskCode1
Weakly Supervised Few-Shot Segmentation Via Meta-Learning0
PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning0
Few-shot Segmentation with Optimal Transport Matching and Message Flow0
A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot SegmentationCode1
Learning to Segment Medical Images from Few-Shot Sparse LabelsCode0
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight TransformerCode1
Learning Meta-class Memory for Few-Shot Semantic SegmentationCode1
Boosting Few-shot Semantic Segmentation with Transformers0
Scale-Aware Graph Neural Network for Few-Shot Semantic SegmentationCode0
Few-Shot Segmentation via Cycle-Consistent TransformerCode1
Anti-aliasing Semantic Reconstruction for Few-Shot Semantic SegmentationCode1
Attentional Prototype Inference for Few-Shot SegmentationCode0
SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes0
Adaptive Prototype Learning and Allocation for Few-Shot SegmentationCode1
Hypercorrelation Squeeze for Few-Shot SegmentationCode1
Self-Guided and Cross-Guided Learning for Few-Shot SegmentationCode1
Mining Latent Classes for Few-shot SegmentationCode1
Harmonic Feature Activation for Few-Shot Semantic SegmentationCode1
Hypercorrelation Squeeze for Few-Shot Segmenation0
Few-Shot Semantic Segmentation With Cyclic Memory Network0
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?Code1
Prototype-based Incremental Few-Shot Semantic SegmentationCode1
Generalized Few-shot Semantic SegmentationCode1
SML: Semantic Meta-learning for Few-shot Semantic Segmentation0
Prototype Mixture Models for Few-shot Semantic SegmentationCode1
Prior Guided Feature Enrichment Network for Few-Shot SegmentationCode1
Few-Shot Semantic Segmentation with Democratic Attention Networks0
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without AnnotationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SegGPT (ViT)Mean IoU83.2Unverified
2DCAMA (ResNet-101)FB-IoU77.6Unverified
3PGMA-Net (ResNet-101)Mean IoU77.6Unverified
4PGMA-Net (ResNet-50)Mean IoU74.1Unverified
5PGMA-Net (ViT-B/16)Mean IoU74.1Unverified
6GF-SAM (DINOv2)Mean IoU72.1Unverified
7HMNet (ResNet-50)Mean IoU70.4Unverified
8AENet (ResNet-50)Mean IoU70.3Unverified
9HDMNet (DifFSS, ResNet-50)Mean IoU70.2Unverified
10VAT + MSI (ResNet-101)Mean IoU70.1Unverified
#ModelMetricClaimedVerifiedStatus
1SegGPT (ViT)Mean IoU89.8Unverified
2GF-SAM (DINOv2)Mean IoU82.6Unverified
3PGMA-Net (ResNet-101)Mean IoU78.6Unverified
4FPTrans (DeiT-B/16)Mean IoU78Unverified
5DGPNet (ResNet-101)Mean IoU75.4Unverified
6PGMA-Net (ResNet-50)Mean IoU75.2Unverified
7DCAMA (Swin-B)Mean IoU74.9Unverified
8PGMA-Net (ViT-B/16)Mean IoU74.6Unverified
9AENet (ResNet-50)Mean IoU74.2Unverified
10HMNet (ResNet-50)Mean IoU74.1Unverified