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https://github.com/WingkeungM/Awesome-Few-Shot-Semantic-Segmentation

Collect some papers about few shot semantic segmentation.
https://github.com/WingkeungM/Awesome-Few-Shot-Semantic-Segmentation
List: Awesome-Few-Shot-Semantic-Segmentation
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Collect some papers about few shot semantic segmentation.
Host: GitHub
URL: https://github.com/WingkeungM/Awesome-Few-Shot-Semantic-Segmentation
Owner: WingkeungM
Created: 2022-04-04T06:59:09.000Z (over 2 years ago)
Default Branch: main
Last Pushed: 2023-01-15T14:58:40.000Z (almost 2 years ago)
Last Synced: 2024-06-20T15:47:23.114Z (6 months ago)
Size: 47.9 KB
Stars: 44
Watchers: 4
Forks: 4
Open Issues: 1
Metadata Files:
- Readme: README.md
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README

        # Awesome-Few-Shot-Semantic-Segmentation

Collect some papers about few shot semantic segmentation for images and point cloud.

Some papers for 2017-2021 refer to [Few-Shot-Semantic-Segmentation-Papers](https://github.com/xiaomengyc/Few-Shot-Semantic-Segmentation-Papers).

Statistics: 🔥 code is available & stars >= 100  |  ⭐ citation >= 50

## Point Cloud Semantic Segmentation

## 2021

| Title | Venue | Dataset | PDF | CODE |

| :-----|:-----:|:---:|:---:|:----:|

| Few-shot 3D Point Cloud Semantic Segmentation 🔥  | CVPR | S3DIS & ScanNet | [PDF](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhao_Few-Shot_3D_Point_Cloud_Semantic_Segmentation_CVPR_2021_paper.pdf) | [CODE](https://github.com/Na-Z/attMPTI) |

| Compositional Prototype Network with Multi-view Comparision for Few-Shot Point Cloud Semantic Segmentation | arXiv | ScanNet | [PDF](https://arxiv.org/pdf/2012.14255.pdf) | - |

| Few-shot Learning of Part-specific Probability Space for 3D Shape Segmentation | CVPR | ShapeNetPart | [PDF](https://openaccess.thecvf.com/content_CVPR_2020/papers/Wang_Few-Shot_Learning_of_Part-Specific_Probability_Space_for_3D_Shape_Segmentation_CVPR_2020_paper.pdf) | [CODE](https://github.com/Lingjing324/Few-Shot-Learning-of-Part-Specific-Probability-Space-for-3D-Shape-Segmentation) |

## Image Semantic Segmentation

## 2022

| Title | Venue | Dataset | PDF | CODE |

| :-----|:-----:|:---:|:---:|:----:|

| Mask Matching Transformer for Few-Shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2301.01208.pdf) | [CODE]() |

| MSI: Maximize Support-Set Information for Few-Shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2212.04673.pdf) | [CODE]() |

| A Strong Baseline for Generalized Few-Shot Semantic Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.14126.pdf) | [CODE]() |

| Elimination of Non-Novel Segments at Multi-Scale for Few-Shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.02300.pdf) | [CODE]() |

| A Joint Framework Towards Class-aware and Class-agnostic Alignment for Few-shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.01310.pdf) | [CODE]() |

| Feature-Proxy Transformer for Few-Shot Segmentation | NIPS2022 | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2210.06908.pdf) | [CODE]() |

| Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation | NIPS2022 | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2210.06780.pdf) | [CODE]() |

| Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation | ECCV | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2208.00306.pdf) | [CODE]() |

| Self-Support Few-Shot Semantic Segmentation | ECCV | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2207.11549.pdf) | [CODE]() |

| Cost Aggregation with 4D Convolutional Swin Transformer for Few-Shot Segmentation | ECCV | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2207.10866.pdf) | [CODE]() |

| Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentatio | ECCV | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2207.08549.pdf) | [CODE]() |

| MSANet: Multi-Similarity and Attention Guidance for Boosting Few-Shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2206.09667.pdf) | [CODE]() |

| Singular Value Fine-tuning: Few-shot Segmentation requires Few-parameters Fine-tuning | NIPS2022 | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2206.06122.pdf) | [CODE]() |

| Learning Non-target Knowledge for Few-shot Semantic Segmentation | CVPR | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2205.04903.pdf) | [CODE]() |

| CATrans: Context and Affinity Transformer for Few-Shot Segmentation | IJCAI | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2204.12817.pdf) | [CODE]() |

| Dynamic Prototype Convolution Network for Few-Shot Semantic Segmentation | CVPR | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2204.10638.pdf) | [CODE]() |

| Progressively Dual Prior Guided Few-shot Semantic Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.15467.pdf) | [CODE]() |

| Activating the Discriminability of Novel Classes for Few-shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2212.01131.pdf) | [CODE]() |

| Interclass Prototype Relation for Few-Shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.08681.pdf) | [CODE]() |

| Elimination of Non-Novel Segments at Multi-Scale for Few-Shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.02300.pdf) | [CODE]() |

| A Joint Framework Towards Class-aware and Class-agnostic Alignment for Few-shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2211.01310.pdf) | [CODE]() |

| Feature-Proxy Transformer for Few-Shot Segmentation | NeurIPS 2022 | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2210.06908.pdf) | [CODE](https://github.com/Jarvis73/FPTrans) |

| Intermediate Prototype Mining Transformer for Few-Shot Semantic Segmentation | NeurIPS 2022 | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2210.06780.pdf) | [CODE]() |

| Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation | arXiv | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2208.00306.pdf) | [CODE](https://github.com/ShadowXZT/DACM-Few-shot.pytorch) |

| Learning What Not to Segment: A New Perspective on Few-Shot Segmentation 🔥 | CVPR (Oral) | PASCAL & MS COCO | [PDF](https://arxiv.org/pdf/2203.07615v2.pdf) | [CODE](https://github.com/chunbolang/BAM) |

| Holistic Prototype Activation for Few-Shot Segmentation | TPAMI | PASCAL & MS COCO | PDF | [CODE](https://github.com/chunbolang/HPA) |

| Beyond the Prototype: Divide-and-conquer Proxies for Few-shot Segmentation | IJCAI | PASCAL & MS COCO | [PDF](https://arxiv.org/abs/2204.09903.pdf) | [CODE](https://github.com/chunbolang/DCP) |

| Cost Aggregation Is All You Need for Few-Shot Segmentation | arXiv | PASCAL & MS COCO & FSS-1000 | [PDF](https://arxiv.org/pdf/2112.11685.pdf) | [CODE](https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer) |

| MaskSplit: Self-supervised Meta-learning for Few-shot Semantic Segmentation | WACV | PASCAL & MS COCO | [PDF](https://openaccess.thecvf.com/content/WACV2022/papers/Amac_MaskSplit_Self-Supervised_Meta-Learning_for_Few-Shot_Semantic_Segmentation_WACV_2022_paper.pdf) | [CODE](https://github.com/AhmetSencan/MaskSplit-Self-supervised-Meta-learning-for-Few-shot-Semantic-Segmentation) |

| A Pixel-Level Meta-Learner for Weakly Supervised Few-Shot Semantic Segmentation | WACV | PASCAL & MS COCO | [PDF](https://openaccess.thecvf.com/content/WACV2022/papers/Lee_A_Pixel-Level_Meta-Learner_for_Weakly_Supervised_Few-Shot_Semantic_Segmentation_WACV_2022_paper.pdf) | - |

## 2021

| Title | Venue | PDF | CODE |

| :-----|:-----:|:---:|:----:|

| Few-Shot Segmentation via Cycle-Consistent Transformer | NeurIPS | [PDF](https://proceedings.neurips.cc/paper/2021/file/b8b12f949378552c21f28deff8ba8eb6-Paper.pdf) | [CODE](https://github.com/GengDavid/CyCTR) | 

| Part-Based Semantic Transform for Few-Shot Semantic Segmentation | TNNLS | [PDF](https://ieeexplore.ieee.org/document/9448305) | [CODE](https://github.com/Yang-Bob/PST) |

| Scale-Aware Detailed Matching for Few-Shot Aerial Image Semantic Segmentation | TGRS | [PDF](https://ieeexplore.ieee.org/abstract/document/9568898) | [CODE](https://github.com/caoql98/SDM) |

| Rich Embedding Features for One-Shot Semantic Segmentation | TNNLS | [PDF](https://ieeexplore.ieee.org/abstract/document/9463398) | - |

| Simpler is Better: Few-shot Semantic Segmentation with Classifier Weight Transformer| ICCV | [PDF](https://arxiv.org/pdf/2108.03032.pdf) | [CODE](https://github.com/zhiheLu/CWT-for-FSS) |

| Hypercorrelation Squeeze for Few-Shot Segmenation 🔥 | ICCV | [PDF](https://arxiv.org/pdf/2104.01538.pdf) | [CODE](https://github.com/juhongm999/hsnet) |

| Mining Latent Classes for Few-shot Segmentation | ICCV | [PDF](https://arxiv.org/pdf/2103.15402.pdf) | [CODE](https://github.com/LiheYoung/MiningFSS) |

| Few-Shot Semantic Segmentation with Cyclic Memory Network | ICCV | [PDF](https://openaccess.thecvf.com/content/ICCV2021/papers/Xie_Few-Shot_Semantic_Segmentation_With_Cyclic_Memory_Network_ICCV_2021_paper.pdf) | - |

| Learning Meta-class Memory for Few-Shot Semantic Segmentation | ICCV | [PDF](https://openaccess.thecvf.com/content/ICCV2021/papers/Wu_Learning_Meta-Class_Memory_for_Few-Shot_Semantic_Segmentation_ICCV_2021_paper.pdf) | [CODE](https://github.com/wu-zhonghua/MM-Net) |

| Progressive One-Shot Human Parsing | AAAI | [PDF](https://arxiv.org/pdf/2012.11810.pdf) | [CODE](https://github.com/Charleshhy/One-shot-Human-Parsing) |

| Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation | AAAI | [PDF](https://ojs.aaai.org/index.php/AAAI/article/view/16275) | [CODE](https://github.com/oopil/3D_medical_image_FSS) |

| Scale-Aware Graph Neural Network for Few-Shot Semantic Segmentation | CVPR | [PDF](https://openaccess.thecvf.com/content/CVPR2021/papers/Xie_Scale-Aware_Graph_Neural_Network_for_Few-Shot_Semantic_Segmentation_CVPR_2021_paper.pdf) | - |

| Anti-aliasing Semantic Reconstruction for Few-Shot Semantic Segmentation | CVPR | [PDF](https://openaccess.thecvf.com/content/CVPR2021/papers/Liu_Anti-Aliasing_Semantic_Reconstruction_for_Few-Shot_Semantic_Segmentation_CVPR_2021_paper.pdf) | - |

| Adaptive Prototype Learning and Allocation for Few-Shot Segmentation | CVPR | [PDF](https://arxiv.org/pdf/2104.01893.pdf) | [CODE](https://github.com/Reagan1311/ASGNet) |

| Self-Guided and Cross-Guided Learning for Few-Shot Segmentation | CVPR | [PDF](https://arxiv.org/pdf/2103.16129.pdf) | [CODE](https://github.com/zbf1991/SCL) |

| Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? | CVPR  | [PDF](https://arxiv.org/pdf/2012.06166.pdf) | [CODE](https://github.com/mboudiaf/RePRI-for-Few-Shot-Segmentation) |

| On the Texture Bias for Few-Shot CNN Segmentation | WACV | [PDF](https://arxiv.org/pdf/2003.04052v1.pdf) | [CODE](https://github.com/rezazad68/fewshot-segmentation) |

| Harmonic Feature Activation for Few-shot Semantic Segmentation | TIP | [PDF](https://ieeexplore.ieee.org/document/9356450) | [CODE](https://github.com/Bibikiller/HFA) |

| A Location-Sensitive Local Prototype Network for Few-Shot Medical Image Segmentation | ISBI | [PDF](https://arxiv.org/pdf/2103.10178.pdf) | - |

| Dense Gaussian Processes for Few-Shot Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2110.03674.pdf) | - |

| End-to-end One-shot Human Parsing | arXiv | [PDF](https://arxiv.org/pdf/2105.01241.pdf) | - |

| Few-Shot Segmentation with Global and Local Contrastive Learning | arXiv | [PDF](https://arxiv.org/pdf/2108.05293.pdf) | - |

| Few-shot Segmentation with Optimal Transport Matching and Message Flow | arXiv | [PDF](https://arxiv.org/pdf/2108.08518.pdf) | - |

| Uncertainty-Aware Semi-Supervised Few Shot Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2110.08954.pdf) | - |

| Cost Aggregation Is All You Need for Few-Shot Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2112.11685.pdf) | [CODE](https://github.com/Seokju-Cho/Volumetric-Aggregation-Transformer) |

## 2020

| Title | Venue | PDF | CODE |

| :-----|:-----:|:---:|:----:|

| Dynamic Extension Nets for Few-shot Semantic Segmentation | MM | [PDF](https://dl.acm.org/doi/abs/10.1145/3394171.3413915) | [CODE](https://github.com/lizhaoliu-Lec/DENet) |

| Semi-supervised few-shot learning for medical image segmentation | arXiv | [PDF](https://arxiv.org/pdf/2003.08462.pdf) | [CODE](https://github.com/fayjie92/FSMS-Surrogate) |

| Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need? 🔥 | arXiv | [PDF](https://arxiv.org/pdf/2012.06166.pdf) | [CODE](https://github.com/mboudiaf/RePRI-for-Few-Shot-Segmentation) |

| Meta-Learning Initializations for Image Segmentation | NeurIPS-W | [PDF](https://meta-learn.github.io/2020/papers/44_paper.pdf) | [CODE](https://github.com/ml4ai/mliis) |

| BriNet: Towards Bridging the Intra-class and Inter-class Gaps in One-Shot Segmentation | arXiv |[PDF](https://arxiv.org/pdf/2008.06226.pdf) | [CODE](https://github.com/Wi-sc/BriNet) |

| Self-Supervision with Superpixels: Training Few-shot Medical Image Segmentation without Annotation 🔥 ⭐ | ECCV | [PDF](https://arxiv.org/pdf/2007.09886v2.pdf) | [CODE](https://github.com/cheng-01037/Self-supervised-Fewshot-Medical-Image-Segmentation) |

| Generalized Few-Shot Semantic Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2010.05210.pdf) | - |

| FSS-1000: A 1000-Class Dataset for Few-Shot Segmentation 🔥 ⭐ | CVPR | [PDF](https://openaccess.thecvf.com/content_CVPR_2020/papers/Li_FSS-1000_A_1000-Class_Dataset_for_Few-Shot_Segmentation_CVPR_2020_paper.pdf) | [CODE](https://github.com/HKUSTCV/FSS-1000) |

| Few-Shot Semantic Segmentation with Democratic Attention Networks ⭐ | ECCV | [PDF](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123580715.pdf) | - |

| Prototype Mixture Models for Few-shot Semantic Segmentation 🔥 ⭐ | ECCV | [PDF](https://arxiv.org/pdf/2008.03898.pdf) | [CODE](https://github.com/Yang-Bob/PMMs) |

| PFENet: Prior Guided Feature Enrichment Network for Few-shot Segmentation 🔥 ⭐ | TPAMI | [PDF](https://arxiv.org/pdf/2008.01449.pdf) | [CODE](https://github.com/Jia-Research-Lab/PFENet) |

| Part-aware Prototype Network for Few-shot Semantic Segmentation ⭐ | ECCV | [PDF](https://arxiv.org/pdf/2007.06309.pdf) | [CODE](https://github.com/Xiangyi1996/PPNet-PyTorch) |

| SimPropNet: Improved Similarity Propagation for Few-shot Image Segmentation | IJCAI | [PDF](https://arxiv.org/pdf/2004.15014.pdf) | - |

| Objectness-Aware One-Shot Semantic Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2004.02945.pdf) | - |

| Self-Supervised Tuning for Few-Shot Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2004.05538.pdf) | - |

| SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation 🔥 ⭐ | TCYB | [PDF](https://arxiv.org/abs/1810.09091) | [CODE](https://github.com/xiaomengyc/SG-One)|

| CAFENet: Class-Agnostic Few-Shot Edge Detection Network | arXiv | [PDF](https://arxiv.org/pdf/2003.08235.pdf) | - |

| FGN: Fully Guided Network for Few-Shot Instance Segmentation | CVPR | [PDF](https://arxiv.org/pdf/2003.13954.pdf) | - |

| CRNet: Cross-Reference Networks for Few-Shot Segmentation ⭐ | CVPR | [PDF](https://arxiv.org/pdf/2003.10658.pdf) | - |

| Differentiable Meta-learning Model for Few-shot Semantic Segmentation | AAAI | [PDF](https://arxiv.org/pdf/1911.10371.pdf) | - |

| Prototype Refinement Network for Few-Shot Segmentation | arXiv | [PDF](https://arxiv.org/pdf/2002.03579.pdf) | - |

| Weakly Supervised Few-shot Object Segmentation using Co-Attention with Visual and Semantic Embeddings | IJCAI | [PDF](https://www.ijcai.org/Proceedings/2020/0120.pdf) | - |

## 2019

| Title | Venue | PDF | CODE |

| :-----|:-----:|:---:|:----:|

| A deep one-shot network for query-based logo retrieval | PR | [PDF](https://arxiv.org/pdf/1811.01395.pdf) | - |

| PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment 🔥 ⭐ | ICCV | [PDF](http://openaccess.thecvf.com/content_ICCV_2019/papers/Wang_PANet_Few-Shot_Image_Semantic_Segmentation_With_Prototype_Alignment_ICCV_2019_paper.pdf) | [CODE](https://github.com/kaixin96/PANet) |

| Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic Segmentation  ⭐ | ICCV | [PDF](http://openaccess.thecvf.com/content_ICCV_2019/papers/Zhang_Pyramid_Graph_Networks_With_Connection_Attentions_for_Region-Based_One-Shot_Semantic_ICCV_2019_paper.pdf)| - |

| AMP: Adaptive Masked Proxies for Few-Shot Segmentation 🔥 ⭐ | ICCV | [PDF](http://openaccess.thecvf.com/content_ICCV_2019/papers/Siam_AMP_Adaptive_Masked_Proxies_for_Few-Shot_Segmentation_ICCV_2019_paper.pdf) | [CODE](https://github.com/MSiam/AdaptiveMaskedProxies) |

| Feature Weighting and Boosting for Few-Shot Segmentation ⭐ |  ICCV | [PDF](http://openaccess.thecvf.com/content_ICCV_2019/papers/Nguyen_Feature_Weighting_and_Boosting_for_Few-Shot_Segmentation_ICCV_2019_paper.pdf) | - |

| CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot Learning 🔥 ⭐ | CVPR | [PDF](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhang_CANet_Class-Agnostic_Segmentation_Networks_With_Iterative_Refinement_and_Attentive_Few-Shot_CVPR_2019_paper.pdf) | [CODE](https://github.com/icoz69/CaNet) |

| Adaptive Masked Weight Imprinting for Few-Shot Segmentation | ICLRW | [PDF](https://openreview.net/pdf?id=SkeoV4yZUV) | - |

| A New Local Transformation Module for Few-Shot Segmentation | MMMM | [PDF](https://link.springer.com/chapter/10.1007/978-3-030-37734-2_7) |

| A New Few-shot Segmentation Network Based on Class Representation | arXiv | [PDF](https://arxiv.org/pdf/1909.08754.pdf) |

## 2018

| Title | Venue | PDF | CODE |

| :-----|:-----:|:---:|:----:|

| Conditional networks for few-shot semantic segmentation 🔥 ⭐ | ICLRW | [PDF](https://openreview.net/pdf?id=SkMjFKJwG) |  [CODE](https://github.com/shelhamer/revolver)  |

| Few-Shot Semantic Segmentation with Prototype Learning ⭐ | BMVC | [PDF](http://bmvc2018.org/contents/papers/0255.pdf) | - |

## 2017

| Title | Venue | PDF | CODE |

| :-----|:-----:|:---:|:----:|

| One-Shot Learning for Semantic Segmentation 🔥 ⭐ | BMVC | [PDF](https://arxiv.org/abs/1709.03410) | [CODE](https://github.com/lzzcd001/OSLSM) |