主要是自然图像上的小样本分割,医学图像上的将另开一帖。
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One-Shot Learning for Semantic Segmentation(BMVC2017)
开源代码
Few-Shot Semantic Segmentation with Prototype Learning(BMVC2018)
暂未开源
Conditional networks for few-shot semantic segmentation(ICLR2018 Workshop)
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Attention-Based Multi-Context Guiding for Few-Shot Semantic Segmentation (AAAI2019)
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CANet: Class-agnostic segmentation networks with iterative refinement and attentive few-shot learning(CVPR2019)
开源代码
Pyramid Graph Networks with Connection Attentions for Region-Based One-Shot Semantic Segmentation(ICCV2019)
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PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment(ICCV2019)
开源代码
CRNet: Cross-Reference Networks for Few-Shot Segmentation(CVPR2020)
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SG-One: Similarity Guidance Network for One-Shot Semantic Segmentation(IEEE Transactions on Cybernetics 2020)
开源代码
Prior Guided Feature Enrichment Network for Few-Shot Segmentation(TAMI2020)
开源代码
Part-aware Prototype Network for Few-shot Semantic Segmentation(ECCV2020)
开源代码
Few-Shot Semantic Segmentation with Democratic Attention Networks(ECCV2020)
暂未开源
Self-Guided and Cross-Guided Learning for Few-Shot Segmentation(CVPR2021)
开源代码
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation(CVPR2021)
开源代码
Few-Shot Segmentation Without Meta-Learning: A Good Transductive Inference Is All You Need?(CVPR2021)
开源代码
Mining Latent Classes for Few-shot Segmentation(arxiv)
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Deep Gaussian Processes for Few-Shot Segmentation(arxiv)
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Hypercorrelation Squeeze for Few-Shot Segmenation(arxiv)
开源代码
SCNet: Enhancing Few-Shot Semantic Segmentation by Self-Contrastive Background Prototypes(arxiv)
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Few-Shot Segmentation via Cycle-Consistent Transformer(arxiv)
暂未开源