Few Shot Semantic Segmentation Papers [](https://awesome.re)

September 11, 2023 ยท View on GitHub

NOTE: If your paper is not in the list, plese feel free to raise an issue or drop me an e-mail.

2023

TitleVenuePDFCODE
A Strong Baseline for Generalized Few-Shot Semantic SegmentationCVPRPDFCODE
Few Shot Semantic Segmentation: a review of methodologies and open challengesarXivPDF-
Elimination of Non-Novel Segments at Multi-Scale for Few-Shot SegmentationWACVPDF-

2022

TitleVenuePDFCODE
Few-shot Medical Image Segmentation with Cycle-resemblance AttentionWACVPDF-
Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuningNeurIPSPDFCODE
Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot SegmentationECCVPDFCODE
Cross-Domain Few-Shot Semantic SegmentationECCVPDFCODE
Self-Support Few-Shot Semantic SegmentationECCVPDFCODE
Interclass Prototype Relation for Few-Shot SegmentationECCVPDFCODE
Generalized Few-shot Semantic SegmentationCVPRPDFCODE
Integrative Few-Shot Learning for Classification and SegmentationCVPRPDFCODE
Learning What Not to Segment: A New Perspective on Few-Shot SegmentationCVPRPDFCODE
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic SegmentationTMMPDF-
MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot SegmentationarXivPDFCODE

2021

TitleVenuePDFCODE
Few-shot Semantic Segmentation with Self-supervision from Pseudo-classesBMVCPDFCODE
Rich Embedding Features for One-Shot Semantic SegmentationTNNLSPDF-
Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight TransformerICCVPDFCODE
Hypercorrelation Squeeze for Few-Shot SegmentationICCVPDFCODE
Mining Latent Classes for Few-shot SegmentationICCVPDFCODE
Few-Shot Semantic Segmentation with Cyclic Memory NetworkICCVPDF-
Learning Meta-class Memory for Few-Shot Semantic SegmentationICCVPDFCODE
Progressive One-Shot Human ParsingAAAIPDFCODE
Bidirectional RNN-based Few Shot Learning for 3D Medical Image SegmentationAAAIPDFCODE
Scale-Aware Graph Neural Network for Few-Shot Semantic SegmentationCVPRPDF-
Adaptive Prototype Learning and Allocation for Few-Shot SegmentationCVPRPDFCODE
Self-Guided and Cross-Guided Learning for Few-Shot SegmentationCVPRPDFCODE
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?CVPRPDFCODE
On the Texture Bias for Few-Shot CNN SegmentationWACVPDFCODE
A Location-Sensitive Local Prototype Network for Few-Shot Medical Image SegmentationISBIPDF-
Dense Gaussian Processes for Few-Shot SegmentationarXivPDF-
End-to-end One-shot Human ParsingarXivPDF-
Few-Shot Segmentation with Global and Local Contrastive LearningarXivPDF-
Few-shot Segmentation with Optimal Transport Matching and Message FlowarXivPDF-
Uncertainty-Aware Semi-Supervised Few Shot SegmentationarXivPDF-

2020

TitleVenuePDFCODE
Prior Guided Feature Enrichment Network for Few-Shot SegmentationTPAMIPDFCODE
Dynamic Extension Nets for Few-shot Semantic SegmentationMMPDFCODE
Semi-supervised few-shot learning for medical image segmentationarXivPDFCODE
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?arXivPDFCODE
Meta-Learning Initializations for Image SegmentationNeurIPS-WPDFCODE
BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot SegmentationarXivPDFCODE
Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without AnnotationECCVPDFCODE
Generalized Few-Shot Semantic SegmentationarXivPDF-
FSS-1000: A 1000-Class Dataset for Few-Shot SegmentationCVPRPDFCODE
Few-Shot Semantic Segmentation with Democratic Attention NetworksECCVPDF-
Prototype Mixture Models for Few-shot Semantic SegmentationECCVPDFCODE
PFENet: Prior Guided Feature Enrichment Network for Few-shot SegmentationTPAMIPDFCODE
Part-aware Prototype Network for Few-shot Semantic SegmentationECCVPDFCODE
SimPropNet: Improved Similarity Propagation for Few-shot Image SegmentationIJCAIPDF-
Objectness-Aware One-Shot Semantic SegmentationarXivPDF-
Self-Supervised Tuning for Few-Shot SegmentationarXivPDF-
SG-One: Similarity Guidance Network for One-Shot Semantic SegmentationTCYBPDFCODE
CAFENet: Class-Agnostic Few-Shot Edge Detection NetworkarXivPDF-
FGN: Fully Guided Network for Few-Shot Instance SegmentationCVPRPDF-
CRNet: Cross-Reference Networks for Few-Shot SegmentationCVPRPDF-
Differentiable Meta-learning Model for Few-shot Semantic SegmentationAAAIPDF-
Prototype Refinement Network for Few-Shot SegmentationarXivPDF-
Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic EmbeddingsIJCAIPDF-

2019

TitleVenuePDFCODE
Attention-Based Multi-Context Guiding for Few-Shot Semantic SegmentationAAAIPDFCODE
A deep one-shot network for query-based logo retrievalPRPDF-
PANet: Few-Shot Image Semantic Segmentation with Prototype AlignmentICCVPDFCODE
Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic SegmentationICCVPDF-
AMP: Adaptive Masked Proxies for Few-Shot SegmentationICCVPDFCODE
Feature Weighting and Boosting for Few-Shot SegmentationICCVPDF-
CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot LearningCVPRPDFCODE
Adaptive Masked Weight Imprinting for Few-Shot SegmentationICLRWPDF-
A New Local Transformation Module for Few-Shot SegmentationMMMMPDF
A New Few-shot Segmentation Network Based on Class RepresentationarXivPDF

2018

TitleVenuePDFCODE
Conditional networks for few-shot semantic segmentationICLRWPDFCODE
Few-Shot Semantic Segmentation with Prototype LearningBMVCPDF-

2017

TitleVenuePDFCODE
One-Shot Learning for Semantic SegmentationBMVCPDFCODE