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 101–150 of 168 papers

TitleStatusHype
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
Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation—0
Prediction Calibration for Generalized Few-shot Semantic Segmentation—0
Progressively Dual Prior Guided Few-shot Semantic Segmentation—0
Prototypical Kernel Learning and Open-set Foreground Perception for Generalized Few-shot Semantic Segmentation—0
Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation—0
Reflection Invariance Learning for Few-shot Semantic Segmentation—0
Relevant Intrinsic Feature Enhancement Network for Few-Shot Semantic Segmentation—0
Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer—0
SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes—0
SegGPT: Towards Segmenting Everything in Context—0
Segment Any Class (SAC): Multi-Class Few-Shot Semantic Segmentation via Class Region Proposals—0
Self-guided Few-shot Semantic Segmentation for Remote Sensing Imagery Based on Large Vision Models—0
Self-Regularized Prototypical Network for Few-Shot Semantic Segmentation—0
Show and Grasp: Few-shot Semantic Segmentation for Robot Grasping through Zero-shot Foundation Models—0
SML: Semantic Meta-learning for Few-shot Semantic Segmentation—0
Target-aware Bi-Transformer for Few-shot Segmentation—0
Task Consistent Prototype Learning for Incremental Few-shot Semantic Segmentation—0
Texture based Prototypical Network for Few-Shot Semantic Segmentation of Forest Cover: Generalizing for Different Geographical Regions—0
Unsupervised augmentation optimization for few-shot medical image segmentation—0
Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond—0
Weakly Supervised Few-Shot Segmentation Via Meta-Learning—0
A dense subgraph based algorithm for compact salient image region detectionCode0
RobustEMD: Domain Robust Matching for Cross-domain Few-shot Medical Image SegmentationCode0
Scale-Aware Graph Neural Network for Few-Shot Semantic SegmentationCode0
Adaptive Masked Proxies for Few-Shot SegmentationCode0
Dual Prototypical Contrastive Learning for Few-shot Semantic SegmentationCode0
Unlocking the Potential of Pre-trained Vision Transformers for Few-Shot Semantic Segmentation through Relationship DescriptorsCode0
Learning to Segment Medical Images from Few-Shot Sparse LabelsCode0
Clustered-patch Element Connection for Few-shot LearningCode0
CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot LearningCode0
HM: Hybrid Masking for Few-Shot SegmentationCode0
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot SegmentationCode0
MSI: Maximize Support-Set Information for Few-Shot SegmentationCode0
FSSUWNet: Mitigating the Fragility of Pre-trained Models with Feature Enhancement for Few-Shot Semantic Segmentation in Underwater ImagesCode0
FSS-1000: A 1000-Class Dataset for Few-Shot SegmentationCode0
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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