• Corpus ID: 233423665

Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank

@article{Alonso2021SemiSupervisedSS,
  title={Semi-Supervised Semantic Segmentation with Pixel-Level Contrastive Learning from a Class-wise Memory Bank},
  author={I{\~n}igo Alonso and Alberto Sabater and David Ferstl and Luis Montesano and Ana Cristina Murillo},
  journal={ArXiv},
  year={2021},
  volume={abs/2104.13415}
}
This work presents a novel approach for semi-supervised semantic segmentation. The key element of this approach is our contrastive learning module that enforces the segmentation network to yield similar pixel-level feature representations for same-class samples across the whole dataset. To achieve this, we maintain a memory bank which is continuously updated with relevant and high-quality feature vectors from labeled data. In an end-to-end training, the features from both labeled and unlabeled… 

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