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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 101–150 of 168 papers

TitleStatusHype
Language-guided Few-shot Semantic Segmentation—0
Self-guided Few-shot Semantic Segmentation for Remote Sensing Imagery Based on Large Vision Models—0
Target-aware Bi-Transformer for Few-shot Segmentation—0
Masked Cross-image Encoding for Few-shot Segmentation—0
Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond—0
Prototypical Kernel Learning and Open-set Foreground Perception for Generalized Few-shot Semantic Segmentation—0
FGNet: Towards Filling the Intra-class and Inter-class Gaps for Few-shot Segmentation—0
Dense Affinity Matching for Few-Shot Segmentation—0
Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-Extended Abstract—0
Unsupervised augmentation optimization for few-shot medical image segmentation—0
Reflection Invariance Learning for Few-shot Semantic Segmentation—0
Advancing Incremental Few-shot Semantic Segmentation via Semantic-guided Relation Alignment and Adaptation—0
Quaternion-valued Correlation Learning for Few-Shot Semantic SegmentationCode0
Clustered-patch Element Connection for Few-shot LearningCode0
[CLS] Token is All You Need for Zero-Shot Semantic Segmentation—0
Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges—0
ForamViT-GAN: Exploring New Paradigms in Deep Learning for Micropaleontological Image Analysis—0
Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot SegmentationCode0
A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic SegmentationCode0
Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving—0
Few-shot Semantic Segmentation with Support-induced Graph Convolutional Network—0
SegGPT: Towards Segmenting Everything in Context—0
MSI: Maximize Support-Set Information for Few-Shot SegmentationCode0
Progressively Dual Prior Guided Few-shot Semantic Segmentation—0
Interclass Prototype Relation for Few-Shot Segmentation—0
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise BinarizationCode0
Self-Regularized Prototypical Network for Few-Shot Semantic Segmentation—0
Prediction Calibration for Generalized Few-shot Semantic Segmentation—0
Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes—0
Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation—0
Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation—0
Texture based Prototypical Network for Few-Shot Semantic Segmentation of Forest Cover: Generalizing for Different Geographical Regions—0
HM: Hybrid Masking for Few-Shot SegmentationCode0
Few-shot semantic segmentation via mask aggregationCode0
Remember the Difference: Cross-Domain Few-Shot Semantic Segmentation via Meta-Memory Transfer—0
Generalized Few-Shot Semantic Segmentation: All You Need is Fine-Tuning—0
Meta-Learning via Learning with Distributed Memory—0
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation—0
Dual Prototypical Contrastive Learning for Few-shot Semantic SegmentationCode0
A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation—0
MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning—0
Few-shot Semantic Segmentation with Self-supervision from Pseudo-classesCode0
Weakly Supervised Few-Shot Segmentation Via Meta-Learning—0
PoissonSeg: Semi-Supervised Few-Shot Medical Image Segmentation via Poisson Learning—0
Few-shot Segmentation with Optimal Transport Matching and Message Flow—0
Learning to Segment Medical Images from Few-Shot Sparse LabelsCode0
Boosting Few-shot Semantic Segmentation with Transformers—0
Scale-Aware Graph Neural Network for Few-Shot Semantic SegmentationCode0
Attentional Prototype Inference for Few-Shot SegmentationCode0
SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes—0
Show:102550
← PrevPage 3 of 4Next →
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
2PGMA-Net (ResNet-101)Mean IoU77.6—Unverified
3DCAMA (ResNet-101)FB-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