Mask guided attention for fine-grained patchy image classification

@article{Wang2021MaskGA,
  title={Mask guided attention for fine-grained patchy image classification},
  author={Jun Wang and Xiaohan Yu and Yongsheng Gao},
  journal={ArXiv},
  year={2021},
  volume={abs/2102.02771}
}
In this work, we present a novel mask guided attention (MGA) method for fine-grained patchy image classification. The key challenge of fine-grained patchy image classification lies in two folds, ultra-fine-grained inter-category variances among objects and very few data available for training. This motivates us to consider employing more useful supervision signal to train a discriminative model within limited training samples. Specifically, the proposed MGA integrates a pre-trained semantic… Expand

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