Segment object with few examples by generating pseudo-episodes from unlabeled data with IPE

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Segment object with few examples by generating pseudo-episodes from unlabeled data with IPE

Image to Pseudo-Episode: Boosting Few-Shot Segmentation by Unlabeled Data
arXiv paper abstract https://arxiv.org/abs/2405.08765
arXiv PDF paper https://arxiv.org/pdf/2405.08765

Few-shot segmentation (FSS) aims to train a model which can segment the object from novel classes with a few labeled samples.

… Considering that there are abundant unlabeled data available, it is promising to improve the generalization ability by exploiting these various data.

For leveraging unlabeled data, … propose a novel method, named Image to Pseudo-Episode (IPE), to generate pseudo-episodes from unlabeled data.

… method contains two modules, i.e., the pseudo-label generation module and the episode generation module.

The former module generates pseudo-labels from unlabeled images by the spectral clustering algorithm, and the latter module generates pseudo-episodes from pseudo-labeled images by data augmentation methods.

… method achieves the state-of-the-art performance for FSS.

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