Few Shot Segmentation
arXiv
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2026
| Title | Venue | Year | Link |
|---|---|---|---|
| Adaptive Attention Distillation for Robust Few-Shot Segmentation under Environmental Perturbations | arXiv | 2026 | Link |
| Boosting SAM for Cross-Domain Few-Shot Segmentation via Conditional Point Sparsification | arXiv | 2026 | Link |
| Cross-Domain Few-Shot Segmentation via Multi-view Progressive Adaptation | arXiv | 2026 | Link |
| FALCON: Few-Shot Adversarial Learning for Cross-Domain Medical Image Segmentation | arXiv | 2026 | Link |
| Prototype Learning-Based Few-Shot Segmentation for Low-Light Crack on Concrete Structures | arXiv | 2026 | Link |
| Revealing the Semantic Selection Gap in DINOv3 through Training-Free Few-Shot Segmentation | arXiv | 2026 | Link |
2025
| Title | Venue | Year | Link |
|---|---|---|---|
| AGENet: Adaptive Edge-aware Geodesic Distance Learning for Few-Shot Medical Image Segmentation | arXiv | 2025 | Link |
| Adapter Naturally Serves as Decoupler for Cross-Domain Few-Shot Semantic Segmentation | arXiv | 2025 | Link |
| Adapting In-Domain Few-Shot Segmentation to New Domains without Source Domain Retraining | arXiv | 2025 | Link |
| Automated Measurement of Eczema Severity with Self-Supervised Learning | arXiv | 2025 | Link |
| Balancing Conservatism and Aggressiveness: Prototype-Affinity Hybrid Network for Few-Shot Segmentation | arXiv | 2025 | Link |
| Beyond Visual Cues: Leveraging General Semantics as Support for Few-Shot Segmentation | arXiv | 2025 | Link |
| Bridging Granularity Gaps: Hierarchical Semantic Learning for Cross-domain Few-shot Segmentation | arXiv | 2025 | Link |
| CMP: A Composable Meta Prompt for SAM-Based Cross-Domain Few-Shot Segmentation | arXiv | 2025 | Link |
| CMaP-SAM: Contraction Mapping Prior for SAM-driven Few-shot Segmentation | arXiv | 2025 | Link |
| CoFi: A Fast Coarse-to-Fine Few-Shot Pipeline for Glomerular Basement Membrane Segmentation | arXiv | 2025 | Link |
| Cross-Domain Few-Shot Segmentation via Ordinary Differential Equations over Time Intervals | arXiv | 2025 | Link |
| DFR: A Decompose-Fuse-Reconstruct Framework for Multi-Modal Few-Shot Segmentation | arXiv | 2025 | Link |
| DSV-LFS: Unifying LLM-Driven Semantic Cues with Visual Features for Robust Few-Shot Segmentation | arXiv | 2025 | Link |
| Divide-and-Conquer Decoupled Network for Cross-Domain Few-Shot Segmentation | arXiv | 2025 | Link |
| FS-SAM2: Adapting Segment Anything Model 2 for Few-Shot Semantic Segmentation via Low-Rank Adaptation | arXiv | 2025 | Link |
| Federated Self-Supervised Learning for One-Shot Cross-Modal and Cross-Imaging Technique Segmentation | arXiv | 2025 | Link |
| Few-Shot Segmentation of Historical Maps via Linear Probing of Vision Foundation Models | arXiv | 2025 | Link |
| Few-shot Structure-Informed Machinery Part Segmentation with Foundation Models and Graph Neural Networks | arXiv | 2025 | Link |
| Foreground-Covering Prototype Generation and Matching for SAM-Aided Few-Shot Segmentation | arXiv | 2025 | Link |
| Inter- and Intra-image Refinement for Few Shot Segmentation | arXiv | 2025 | Link |
| MARS: a Multimodal Alignment and Ranking System for Few-Shot Segmentation | arXiv | 2025 | Link |
| Matching-Based Few-Shot Semantic Segmentation Models Are Interpretable by Design | arXiv | 2025 | Link |
| Object-level Correlation for Few-Shot Segmentation | arXiv | 2025 | Link |
| Open-world Point Cloud Semantic Segmentation: A Human-in-the-loop Framework | arXiv | 2025 | Link |
| PPBoost: Progressive Prompt Boosting for Text-Driven Medical Image Segmentation | arXiv | 2025 | Link |
| ProMi: An Efficient Prototype-Mixture Baseline for Few-Shot Segmentation with Bounding-Box Annotations | arXiv | 2025 | Link |
| Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning | arXiv | 2025 | Link |
| SANSA: Unleashing the Hidden Semantics in SAM2 for Few-Shot Segmentation | arXiv | 2025 | Link |
| Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation | arXiv | 2025 | Link |
| Tackling Few-Shot Segmentation in Remote Sensing via Inpainting Diffusion Model | arXiv | 2025 | Link |
| Textual and Visual Guided Task Adaptation for Source-Free Cross-Domain Few-Shot Segmentation | arXiv | 2025 | Link |
| The Devil is in Low-Level Features for Cross-Domain Few-Shot Segmentation | arXiv | 2025 | Link |
| Through the Looking Glass: A Dual Perspective on Weakly-Supervised Few-Shot Segmentation | arXiv | 2025 | Link |
| Tied Prototype Model for Few-Shot Medical Image Segmentation | arXiv | 2025 | Link |
| UINO-FSS: Unifying Representation Learning and Few-shot Segmentation via Hierarchical Distillation and Mamba-HyperCorrelation | arXiv | 2025 | Link |
| Unbiased Semantic Decoding with Vision Foundation Models for Few-shot Segmentation | arXiv | 2025 | Link |
| Unlocking the Power of SAM 2 for Few-Shot Segmentation | arXiv | 2025 | Link |
| VessShape: Few-shot 2D blood vessel segmentation by leveraging shape priors from synthetic images | arXiv | 2025 | Link |
| ViRefSAM: Visual Reference-Guided Segment Anything Model for Remote Sensing Segmentation | arXiv | 2025 | Link |
| Vision and Language Reference Prompt into SAM for Few-shot Segmentation | arXiv | 2025 | Link |
| nnSAM2: nnUNet-Enhanced One-Prompt SAM2 for Few-shot Multi-Modality Segmentation and Composition Analysis of Lumbar Paraspinal Muscles | arXiv | 2025 | Link |
2024
| Title | Venue | Year | Link |
|---|---|---|---|
| Adapt Before Comparison: A New Perspective on Cross-Domain Few-Shot Segmentation | arXiv | 2024 | Link |
| Adaptive Prompt Learning with SAM for Few-shot Scanning Probe Microscope Image Segmentation | arXiv | 2024 | Link |
| AgMTR: Agent Mining Transformer for Few-shot Segmentation in Remote Sensing | arXiv | 2024 | Link |
| Applying ViT in Generalized Few-shot Semantic Segmentation | arXiv | 2024 | Link |
| Beyond Mask: Rethinking Guidance Types in Few-shot Segmentation | arXiv | 2024 | Link |
| Boosting Few-Shot Segmentation via Instance-Aware Data Augmentation and Local Consensus Guided Cross Attention | arXiv | 2024 | Link |
| Bridge the Points: Graph-based Few-shot Segment Anything Semantically | arXiv | 2024 | Link |
| Class Similarity Transition: Decoupling Class Similarities and Imbalance from Generalized Few-shot Segmentation | arXiv | 2024 | Link |
| CrackNex: a Few-shot Low-light Crack Segmentation Model Based on Retinex Theory for UAV Inspections | arXiv | 2024 | Link |
| Cross-Domain Few-Shot Segmentation via Iterative Support-Query Correspondence Mining | arXiv | 2024 | Link |
| DINOv2 based Self Supervised Learning For Few Shot Medical Image Segmentation | arXiv | 2024 | Link |
| Data Adaptive Few-shot Multi Label Segmentation with Foundation Model | arXiv | 2024 | Link |
| Dense Self-Supervised Learning for Medical Image Segmentation | arXiv | 2024 | Link |
| Domain-Rectifying Adapter for Cross-Domain Few-Shot Segmentation | arXiv | 2024 | Link |
| Eliminating Feature Ambiguity for Few-Shot Segmentation | arXiv | 2024 | Link |
| Embedding Generalized Semantic Knowledge into Few-Shot Remote Sensing Segmentation | arXiv | 2024 | Link |
| FCC: Fully Connected Correlation for One-Shot Segmentation | arXiv | 2024 | Link |
| Few-Shot 3D Volumetric Segmentation with Multi-Surrogate Fusion | arXiv | 2024 | Link |
| Few-Shot Medical Image Segmentation with Large Kernel Attention | arXiv | 2024 | Link |
| Gaussian Process Emulators for Few-Shot Segmentation in Cardiac MRI | arXiv | 2024 | Link |
| Generalized Few-Shot Meets Remote Sensing: Discovering Novel Classes in Land Cover Mapping via Hybrid Semantic Segmentation Framework | arXiv | 2024 | Link |
| Generalized Few-Shot Semantic Segmentation in Remote Sensing: Challenge and Benchmark | arXiv | 2024 | Link |
| Generative Model-Based Fusion for Improved Few-Shot Semantic Segmentation of Infrared Images | arXiv | 2024 | Link |
| High-Performance Few-Shot Segmentation with Foundation Models: An Empirical Study | arXiv | 2024 | Link |
| IFSENet : Harnessing Sparse Iterations for Interactive Few-shot Segmentation Excellence | arXiv | 2024 | Link |
| Image Segmentation in Foundation Model Era: A Survey | arXiv | 2024 | Link |
| Image to Pseudo-Episode: Boosting Few-Shot Segmentation by Unlabeled Data | arXiv | 2024 | Link |
| Image-to-Lidar Relational Distillation for Autonomous Driving Data | arXiv | 2024 | Link |
| Improving 3D Few-Shot Segmentation with Inference-Time Pseudo-Labeling | arXiv | 2024 | Link |
| In-context learning for medical image segmentation | arXiv | 2024 | Link |
| Judging from Support-set: A New Way to Utilize Few-Shot Segmentation for Segmentation Refinement Process | arXiv | 2024 | Link |
| LERENet: Eliminating Intra-class Differences for Metal Surface Defect Few-shot Semantic Segmentation | arXiv | 2024 | Link |
| Label Anything: Multi-Class Few-Shot Semantic Segmentation with Visual Prompts | arXiv | 2024 | Link |
| Learnable Prompt for Few-Shot Semantic Segmentation in Remote Sensing Domain | arXiv | 2024 | Link |
| Learning General-Purpose Biomedical Volume Representations using Randomized Synthesis | arXiv | 2024 | Link |
| Learning Robust Correlation with Foundation Model for Weakly-Supervised Few-Shot Segmentation | arXiv | 2024 | Link |
| Lightweight Frequency Masker for Cross-Domain Few-Shot Semantic Segmentation | arXiv | 2024 | Link |
| MLIP: Medical Language-Image Pre-training with Masked Local Representation Learning | arXiv | 2024 | Link |
| More than the Sum of Its Parts: Ensembling Backbone Networks for Few-Shot Segmentation | arXiv | 2024 | Link |
| No Re-Train, More Gain: Upgrading Backbones with Diffusion model for Pixel-Wise and Weakly-Supervised Few-Shot Segmentation | arXiv | 2024 | Link |
| No Time to Train: Empowering Non-Parametric Networks for Few-shot 3D Scene Segmentation | arXiv | 2024 | Link |
| Prompt-and-Transfer: Dynamic Class-aware Enhancement for Few-shot Segmentation | arXiv | 2024 | Link |
| ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models | arXiv | 2024 | Link |
| Prototype Correlation Matching and Class-Relation Reasoning for Few-Shot Medical Image Segmentation | arXiv | 2024 | Link |
| Query-guided Prototype Evolution Network for Few-Shot Segmentation | arXiv | 2024 | Link |
| Rethinking Prior Information Generation with CLIP for Few-Shot Segmentation | arXiv | 2024 | Link |
| Retrieval-augmented Few-shot Medical Image Segmentation with Foundation Models | arXiv | 2024 | Link |
| SAM-Aware Graph Prompt Reasoning Network for Cross-Domain Few-Shot Segmentation | arXiv | 2024 | Link |
| SAMIC: Segment Anything with In-Context Spatial Prompt Engineering | arXiv | 2024 | Link |
| Small Object Few-shot Segmentation for Vision-based Industrial Inspection | arXiv | 2024 | Link |
| Symmetrical Joint Learning Support-query Prototypes for Few-shot Segmentation | arXiv | 2024 | Link |
| TAVP: Task-Adaptive Visual Prompt for Cross-domain Few-shot Segmentation | arXiv | 2024 | Link |
| Toward Robust Canine Cardiac Diagnosis: Deep Prototype Alignment Network-Based Few-Shot Segmentation in Veterinary Medicine | arXiv | 2024 | Link |
| Towards Multi-modality Fusion and Prototype-based Feature Refinement for Clinically Significant Prostate Cancer Classification in Transrectal Ultrasound | arXiv | 2024 | Link |
| Visual Prompting for Generalized Few-shot Segmentation: A Multi-scale Approach | arXiv | 2024 | Link |
2023
| Title | Venue | Year | Link |
|---|---|---|---|
| A Language-Guided Benchmark for Weakly Supervised Open Vocabulary Semantic Segmentation | arXiv | 2023 | Link |
| Adaptive FSS: A Novel Few-Shot Segmentation Framework via Prototype Enhancement | arXiv | 2023 | Link |
| Background Clustering Pre-training for Few-shot Segmentation | arXiv | 2023 | Link |
| Boosting Few-shot 3D Point Cloud Segmentation via Query-Guided Enhancement | arXiv | 2023 | Link |
| Clustered-patch Element Connection for Few-shot Learning | arXiv | 2023 | Link |
| DARNet: Bridging Domain Gaps in Cross-Domain Few-Shot Segmentation with Dynamic Adaptation | arXiv | 2023 | Link |
| Dense Affinity Matching for Few-Shot Segmentation | arXiv | 2023 | Link |
| DenseMP: Unsupervised Dense Pre-training for Few-shot Medical Image Segmentation | arXiv | 2023 | Link |
| Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention | arXiv | 2023 | Link |
| Few-shot Medical Image Segmentation via Cross-Reference Transformer | arXiv | 2023 | Link |
| Few-shot Multispectral Segmentation with Representations Generated by Reinforcement Learning | arXiv | 2023 | Link |
| Focus on Query: Adversarial Mining Transformer for Few-Shot Segmentation | arXiv | 2023 | Link |
| Geometry Aware Field-to-field Transformations for 3D Semantic Segmentation | arXiv | 2023 | Link |
| Harmonizing Base and Novel Classes: A Class-Contrastive Approach for Generalized Few-Shot Segmentation | arXiv | 2023 | Link |
| Hierarchical Dense Correlation Distillation for Few-Shot Segmentation | arXiv | 2023 | Link |
| Hierarchical Dense Correlation Distillation for Few-Shot Segmentation-Extended Abstract | arXiv | 2023 | Link |
| LLaFS: When Large Language Models Meet Few-Shot Segmentation | arXiv | 2023 | Link |
| MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation | arXiv | 2023 | Link |
| Masked Cross-image Encoding for Few-shot Segmentation | arXiv | 2023 | Link |
| Multi-Content Interaction Network for Few-Shot Segmentation | arXiv | 2023 | Link |
| Not Just Learning from Others but Relying on Yourself: A New Perspective on Few-Shot Segmentation in Remote Sensing | arXiv | 2023 | Link |
| One-shot Localization and Segmentation of Medical Images with Foundation Models | arXiv | 2023 | Link |
| Precise Few-shot Fat-free Thigh Muscle Segmentation in T1-weighted MRI | arXiv | 2023 | Link |
| Quaternion-valued Correlation Learning for Few-Shot Semantic Segmentation | arXiv | 2023 | Link |
| Reflection Invariance Learning for Few-shot Semantic Segmentation | arXiv | 2023 | Link |
| RestNet: Boosting Cross-Domain Few-Shot Segmentation with Residual Transformation Network | arXiv | 2023 | Link |
| SLiMe: Segment Like Me | arXiv | 2023 | Link |
| Self-Calibrated Cross Attention Network for Few-Shot Segmentation | arXiv | 2023 | Link |
| Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation with Meta-Learning | arXiv | 2023 | Link |
| Self-Supervised Few-Shot Learning for Ischemic Stroke Lesion Segmentation | arXiv | 2023 | Link |
| Target-aware Bi-Transformer for Few-shot Segmentation | arXiv | 2023 | Link |
| Task-Disruptive Background Suppression for Few-Shot Segmentation | arXiv | 2023 | Link |
| Towards Foundation Models Learned from Anatomy in Medical Imaging via Self-Supervision | arXiv | 2023 | Link |
| Unsupervised Universal Image Segmentation | arXiv | 2023 | Link |
| Unsupervised augmentation optimization for few-shot medical image segmentation | arXiv | 2023 | Link |
| Visual and Textual Prior Guided Mask Assemble for Few-Shot Segmentation and Beyond | arXiv | 2023 | Link |
2022
| Title | Venue | Year | Link |
|---|---|---|---|
| A Joint Framework Towards Class-aware and Class-agnostic Alignment for Few-shot Segmentation | arXiv | 2022 | Link |
| A Strong Baseline for Generalized Few-Shot Semantic Segmentation | arXiv | 2022 | Link |
| Activating the Discriminability of Novel Classes for Few-shot Segmentation | arXiv | 2022 | Link |
| Adversarially Robust Prototypical Few-shot Segmentation with Neural-ODEs | arXiv | 2022 | Link |
| Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels | arXiv | 2022 | Link |
| Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentation | arXiv | 2022 | Link |
| Bidirectional Feature Globalization for Few-shot Semantic Segmentation of 3D Point Cloud Scenes | arXiv | 2022 | Link |
| CATrans: Context and Affinity Transformer for Few-Shot Segmentation | arXiv | 2022 | Link |
| CRCNet: Few-shot Segmentation with Cross-Reference and Region-Global Conditional Networks | arXiv | 2022 | Link |
| CobNet: Cross Attention on Object and Background for Few-Shot Segmentation | arXiv | 2022 | Link |
| Contrastive Enhancement Using Latent Prototype for Few-Shot Segmentation | arXiv | 2022 | Link |
| Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation | arXiv | 2022 | Link |
| Cross-domain Few-shot Segmentation with Transductive Fine-tuning | arXiv | 2022 | Link |
| Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation | arXiv | 2022 | Link |
| Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation | arXiv | 2022 | Link |
| Elimination of Non-Novel Segments at Multi-Scale for Few-Shot Segmentation | arXiv | 2022 | Link |
| Feature-Proxy Transformer for Few-Shot Segmentation | arXiv | 2022 | Link |
| Few-Shot Segmentation via Rich Prototype Generation and Recurrent Prediction Enhancement | arXiv | 2022 | Link |
| HM: Hybrid Masking for Few-Shot Segmentation | arXiv | 2022 | Link |
| Integrative Few-Shot Learning for Classification and Segmentation | arXiv | 2022 | Link |
| Interclass Prototype Relation for Few-Shot Segmentation | arXiv | 2022 | Link |
| Learning What Not to Segment: A New Perspective on Few-Shot Segmentation | arXiv | 2022 | Link |
| MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation | arXiv | 2022 | Link |
| MSI: Maximize Support-Set Information for Few-Shot Segmentation | arXiv | 2022 | Link |
| Mask Matching Transformer for Few-Shot Segmentation | arXiv | 2022 | Link |
| Multi-similarity based Hyperrelation Network for few-shot segmentation | arXiv | 2022 | Link |
| Online Refinement of a Scene Recognition Model for Mobile Robots by Observing Human's Interaction with Environments | arXiv | 2022 | Link |
| PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise Binarization | arXiv | 2022 | Link |
| Progressively Dual Prior Guided Few-shot Semantic Segmentation | arXiv | 2022 | Link |
| Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration | arXiv | 2022 | Link |
| Q-Net: Query-Informed Few-Shot Medical Image Segmentation | arXiv | 2022 | Link |
| Query Semantic Reconstruction for Background in Few-Shot Segmentation | arXiv | 2022 | Link |
| Robust Prototypical Few-Shot Organ Segmentation with Regularized Neural-ODEs | arXiv | 2022 | Link |
| Self-Regularized Prototypical Network for Few-Shot Semantic Segmentation | arXiv | 2022 | Link |
| Self-Support Few-Shot Semantic Segmentation | arXiv | 2022 | Link |
| Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning | arXiv | 2022 | Link |
| Task-Adaptive Feature Transformer with Semantic Enrichment for Few-Shot Segmentation | arXiv | 2022 | Link |
| Texture based Prototypical Network for Few-Shot Semantic Segmentation of Forest Cover: Generalizing for Different Geographical Regions | arXiv | 2022 | Link |
2021
| Title | Venue | Year | Link |
|---|---|---|---|
| A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation | arXiv | 2021 | Link |
| A Self-Distillation Embedded Supervised Affinity Attention Model for Few-Shot Segmentation | arXiv | 2021 | Link |
| Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers | arXiv | 2021 | Link |
| Adaptive Prototype Learning and Allocation for Few-Shot Segmentation | arXiv | 2021 | Link |
| Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation | arXiv | 2021 | Link |
| Attentional Prototype Inference for Few-Shot Segmentation | arXiv | 2021 | Link |
| Boosting Few-shot Semantic Segmentation with Transformers | arXiv | 2021 | Link |
| Cost Aggregation Is All You Need for Few-Shot Segmentation | arXiv | 2021 | Link |
| Deep Gaussian Processes for Few-Shot Segmentation | arXiv | 2021 | Link |
| Dense Gaussian Processes for Few-Shot Segmentation | arXiv | 2021 | Link |
| Few-Shot Segmentation via Cycle-Consistent Transformer | arXiv | 2021 | Link |
| Few-Shot Segmentation with Global and Local Contrastive Learning | arXiv | 2021 | Link |
| Few-shot Segmentation with Optimal Transport Matching and Message Flow | arXiv | 2021 | Link |
| GANORCON: Are Generative Models Useful for Few-shot Segmentation? | arXiv | 2021 | Link |
| Generalized Few-Shot Semantic Segmentation: All You Need is Fine-Tuning | arXiv | 2021 | Link |
| Hypercorrelation Squeeze for Few-Shot Segmentation | arXiv | 2021 | Link |
| Improved Few-shot Segmentation by Redefinition of the Roles of Multi-level CNN Features | arXiv | 2021 | Link |
| Knowledge Transfer for Few-shot Segmentation of Novel White Matter Tracts | arXiv | 2021 | Link |
| Learn to Learn Metric Space for Few-Shot Segmentation of 3D Shapes | arXiv | 2021 | Link |
| Learning Meta-class Memory for Few-Shot Semantic Segmentation | arXiv | 2021 | Link |
| MFNet: Multi-class Few-shot Segmentation Network with Pixel-wise Metric Learning | arXiv | 2021 | Link |
| MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation | arXiv | 2021 | Link |
| Meta-learning with implicit gradients in a few-shot setting for medical image segmentation | arXiv | 2021 | Link |
| Mining Latent Classes for Few-shot Segmentation | arXiv | 2021 | Link |
| PFENet++: Boosting Few-shot Semantic Segmentation with the Noise-filtered Context-aware Prior Mask | arXiv | 2021 | Link |
| Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes | arXiv | 2021 | Link |
| Prototypical Region Proposal Networks for Few-Shot Localization and Classification | arXiv | 2021 | Link |
| Representing Shape Collections with Alignment-Aware Linear Models | arXiv | 2021 | Link |
| Self-Guided and Cross-Guided Learning for Few-Shot Segmentation | arXiv | 2021 | Link |
| Uncertainty-Aware Semi-Supervised Few Shot Segmentation | arXiv | 2021 | Link |
| Weakly Supervised Few-Shot Segmentation Via Meta-Learning | arXiv | 2021 | Link |
2020
| Title | Venue | Year | Link |
|---|---|---|---|
| BiOpt: Bi-Level Optimization for Few-Shot Segmentation | arXiv | 2020 | Link |
| Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation | arXiv | 2020 | Link |
| BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot Segmentation | arXiv | 2020 | Link |
| CRNet: Cross-Reference Networks for Few-Shot Segmentation | arXiv | 2020 | Link |
| Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images | arXiv | 2020 | Link |
| Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? | arXiv | 2020 | Link |
| Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations | arXiv | 2020 | Link |
| Generalized Few-shot Semantic Segmentation | arXiv | 2020 | Link |
| On the Texture Bias for Few-Shot CNN Segmentation | arXiv | 2020 | Link |
| Part-aware Prototype Network for Few-shot Semantic Segmentation | arXiv | 2020 | Link |
| Prior Guided Feature Enrichment Network for Few-Shot Segmentation | arXiv | 2020 | Link |
| Prototype Mixture Models for Few-shot Semantic Segmentation | arXiv | 2020 | Link |
| Prototype Refinement Network for Few-Shot Segmentation | arXiv | 2020 | Link |
| Prototype-based Incremental Few-Shot Semantic Segmentation | arXiv | 2020 | Link |
| Self-Supervised Tuning for Few-Shot Segmentation | arXiv | 2020 | Link |
| SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation | arXiv | 2020 | Link |
| Task-Adaptive Feature Transformer for Few-Shot Segmentation | arXiv | 2020 | Link |
| Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings | arXiv | 2020 | Link |
2019
| Title | Venue | Year | Link |
|---|---|---|---|
| 'Squeeze & Excite' Guided Few-Shot Segmentation of Volumetric Images | arXiv | 2019 | Link |
| A New Few-shot Segmentation Network Based on Class Representation | arXiv | 2019 | Link |
| A New Local Transformation Module for Few-shot Segmentation | arXiv | 2019 | Link |
| Adaptive Masked Proxies for Few-Shot Segmentation | arXiv | 2019 | Link |
| CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning | arXiv | 2019 | Link |
| Differentiable Meta-learning Model for Few-shot Semantic Segmentation | arXiv | 2019 | Link |
| FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation | arXiv | 2019 | Link |
| Feature Weighting and Boosting for Few-Shot Segmentation | arXiv | 2019 | Link |
| Flow Based Self-supervised Pixel Embedding for Image Segmentation | arXiv | 2019 | Link |
| Learn to Segment Organs with a Few Bounding Boxes | arXiv | 2019 | Link |
| Learning Point Embeddings from Shape Repositories for Few-Shot Segmentation | arXiv | 2019 | Link |
| PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment | arXiv | 2019 | Link |
| Unsupervised cycle-consistent deformation for shape matching | arXiv | 2019 | Link |
2018
| Title | Venue | Year | Link |
|---|---|---|---|
| Few-Shot Segmentation Propagation with Guided Networks | arXiv | 2018 | Link |