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