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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

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 61–70 of 168 papers

Title	Date	Tasks	Status	Hype
Harmonic Feature Activation for Few-Shot Semantic Segmentation	Feb 17, 2021	Few-Shot Semantic SegmentationSegmentation	CodeCode Available	1
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?	Dec 11, 2020	AllFew-Shot Semantic Segmentation	CodeCode Available	1
Prototype-based Incremental Few-Shot Semantic Segmentation	Nov 30, 2020	Few-Shot Semantic SegmentationIncremental Learning	CodeCode Available	1
Generalized Few-shot Semantic Segmentation	Oct 11, 2020	Few-Shot Semantic SegmentationGeneralized Few-Shot Semantic Segmentation	CodeCode Available	1
Prototype Mixture Models for Few-shot Semantic Segmentation	Aug 10, 2020	Few-Shot Semantic SegmentationSegmentation	CodeCode Available	1
Prior Guided Feature Enrichment Network for Few-Shot Segmentation	Aug 4, 2020	Few-Shot Semantic SegmentationSemantic Segmentation	CodeCode Available	1
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation	Jul 20, 2020	Cardiac SegmentationFew-Shot Semantic Segmentation	CodeCode Available	1
Part-aware Prototype Network for Few-shot Semantic Segmentation	Jul 13, 2020	Few-Shot Semantic SegmentationGraph Neural Network	CodeCode Available	1
Objectness-Aware Few-Shot Semantic Segmentation	Apr 6, 2020	Few-Shot Semantic SegmentationSegmentation	CodeCode Available	1
On the Texture Bias for Few-Shot CNN Segmentation	Mar 9, 2020	Few-Shot LearningFew-Shot Semantic Segmentation	CodeCode Available	1

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All datasets PASCAL-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

#	Model	Metric	Claimed	Verified	Status
1	SegGPT (ViT)	Mean IoU	83.2	—	Unverified
2	DCAMA (ResNet-101)	FB-IoU	77.6	—	Unverified
3	PGMA-Net (ResNet-101)	Mean IoU	77.6	—	Unverified
4	PGMA-Net (ResNet-50)	Mean IoU	74.1	—	Unverified
5	PGMA-Net (ViT-B/16)	Mean IoU	74.1	—	Unverified
6	GF-SAM (DINOv2)	Mean IoU	72.1	—	Unverified
7	HMNet (ResNet-50)	Mean IoU	70.4	—	Unverified
8	AENet (ResNet-50)	Mean IoU	70.3	—	Unverified
9	HDMNet (DifFSS, ResNet-50)	Mean IoU	70.2	—	Unverified
10	VAT + MSI (ResNet-101)	Mean IoU	70.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	SegGPT (ViT)	Mean IoU	89.8	—	Unverified
2	GF-SAM (DINOv2)	Mean IoU	82.6	—	Unverified
3	PGMA-Net (ResNet-101)	Mean IoU	78.6	—	Unverified
4	FPTrans (DeiT-B/16)	Mean IoU	78	—	Unverified
5	DGPNet (ResNet-101)	Mean IoU	75.4	—	Unverified
6	PGMA-Net (ResNet-50)	Mean IoU	75.2	—	Unverified
7	DCAMA (Swin-B)	Mean IoU	74.9	—	Unverified
8	PGMA-Net (ViT-B/16)	Mean IoU	74.6	—	Unverified
9	AENet (ResNet-50)	Mean IoU	74.2	—	Unverified
10	HMNet (ResNet-50)	Mean IoU	74.1	—	Unverified