A Compositional Feature Embedding and Similarity Metric for Ultra-Fine-Grained Visual Categorization

@article{Sun2021ACF,
  title={A Compositional Feature Embedding and Similarity Metric for Ultra-Fine-Grained Visual Categorization},
  author={Yajie Sun and Miaohua Zhang and Xiaohan Yu and Yi Liao and Yongsheng Gao},
  journal={2021 Digital Image Computing: Techniques and Applications (DICTA)},
  year={2021},
  pages={01-08}
}
Fine-grained visual categorization (FGVC), which aims at classifying objects with small inter-class variances, has been significantly advanced in recent years. However, ultra-fine-grained visual categorization (ultra-FGVC), which targets at identifying subclasses with extremely similar patterns, has not received much attention. In ultra-FGVC datasets, the samples per category are always scarce as the granularity moves down, which will lead to overfitting problems. Moreover, the difference among… 

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