Few Shot Semantic Segmentation Papers

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

2023

| Title | Venue | PDF | CODE | | :-----|:-----:|:---:|:----:| | A Strong Baseline for Generalized Few-Shot Semantic Segmentation | CVPR | PDF | CODE| | Few Shot Semantic Segmentation: a review of methodologies and open challenges | arXiv | PDF | - | | Elimination of Non-Novel Segments at Multi-Scale for Few-Shot Segmentation | WACV | PDF | - |

2022

| Title | Venue | PDF | CODE | | :-----|:-----:|:---:|:----:| | Few-shot Medical Image Segmentation with Cycle-resemblance Attention | WACV | PDF | - | | Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning | NeurIPS | PDF | CODE | | Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation | ECCV | PDF | CODE | | Cross-Domain Few-Shot Semantic Segmentation | ECCV | PDF | CODE | | Self-Support Few-Shot Semantic Segmentation | ECCV | PDF | CODE | | Interclass Prototype Relation for Few-Shot Segmentation | ECCV | PDF | CODE | | Generalized Few-shot Semantic Segmentation | CVPR | PDF | CODE | Integrative Few-Shot Learning for Classification and Segmentation | CVPR | PDF | CODE | | Learning What Not to Segment: A New Perspective on Few-Shot Segmentation | CVPR | PDF | CODE | | APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation | TMM | PDF | - | | MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation | arXiv | PDF | CODE |

2021

| Title | Venue | PDF | CODE | | :-----|:-----:|:---:|:----:| | Few-shot Semantic Segmentation with Self-supervision from Pseudo-classes | BMVC | PDF | CODE | | Rich Embedding Features for One-Shot Semantic Segmentation | TNNLS | PDF | - | | Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer| ICCV | PDF | CODE | | Hypercorrelation Squeeze for Few-Shot Segmentation | ICCV | PDF | CODE | | Mining Latent Classes for Few-shot Segmentation | ICCV | PDF | CODE | | Few-Shot Semantic Segmentation with Cyclic Memory Network | ICCV | PDF | - | | Learning Meta-class Memory for Few-Shot Semantic Segmentation | ICCV | PDF | CODE | | Progressive One-Shot Human Parsing | AAAI | PDF | CODE | | Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation | AAAI | PDF | CODE | | Scale-Aware Graph Neural Network for Few-Shot Semantic Segmentation | CVPR | PDF | - | | Adaptive Prototype Learning and Allocation for Few-Shot Segmentation | CVPR | PDF | CODE | | Self-Guided and Cross-Guided Learning for Few-Shot Segmentation | CVPR | PDF | CODE | | Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? | CVPR | PDF | CODE | | On the Texture Bias for Few-Shot CNN Segmentation | WACV | PDF | CODE | | A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation | ISBI | PDF | - | | Dense Gaussian Processes for Few-Shot Segmentation | arXiv | PDF | - | | End-to-end One-shot Human Parsing | arXiv | PDF | - | | Few-Shot Segmentation with Global and Local Contrastive Learning | arXiv | PDF | - | | Few-shot Segmentation with Optimal Transport Matching and Message Flow | arXiv | PDF | - | | Uncertainty-Aware Semi-Supervised Few Shot Segmentation | arXiv | PDF | - |

2020

| Title | Venue | PDF | CODE | | :-----|:-----:|:---:|:----:| | Prior Guided Feature Enrichment Network for Few-Shot Segmentation | TPAMI | PDF | CODE | | Dynamic Extension Nets for Few-shot Semantic Segmentation | MM | PDF | CODE | | Semi-supervised few-shot learning for medical image segmentation | arXiv | PDF | CODE | | Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? | arXiv | PDF | CODE | | Meta-Learning Initializations for Image Segmentation | NeurIPS-W | PDF | CODE | | BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot Segmentation | arXiv |PDF | CODE | | Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation | ECCV | PDF | CODE | | Generalized Few-Shot Semantic Segmentation | arXiv | PDF | - | | FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation | CVPR | PDF | CODE | | Few-Shot Semantic Segmentation with Democratic Attention Networks | ECCV | PDF | - | | Prototype Mixture Models for Few-shot Semantic Segmentation | ECCV | PDF | CODE | | PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation| TPAMI | PDF | CODE | | Part-aware Prototype Network for Few-shot Semantic Segmentation | ECCV | PDF | CODE | | SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation | IJCAI | PDF | - | | Objectness-Aware One-Shot Semantic Segmentation | arXiv | PDF | - | | Self-Supervised Tuning for Few-Shot Segmentation | arXiv | PDF | - | | SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation | TCYB | PDF | CODE| | CAFENet: Class-Agnostic Few-Shot Edge Detection Network | arXiv | PDF | - | | FGN: Fully Guided Network for Few-Shot Instance Segmentation | CVPR | PDF | - | | CRNet: Cross-Reference Networks for Few-Shot Segmentation | CVPR | PDF | - | | Differentiable Meta-learning Model for Few-shot Semantic Segmentation | AAAI | PDF | - | | Prototype Refinement Network for Few-Shot Segmentation | arXiv | PDF | - | | Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings | IJCAI | PDF | - |

2019

| Title | Venue