Which Looks Like Which: Exploring Inter-class Relationships in Fine-Grained Visual Categorization

@inproceedings{Pu2014WhichLL,
  title={Which Looks Like Which: Exploring Inter-class Relationships in Fine-Grained Visual Categorization},
  author={Jian Pu and Yu-Gang Jiang and Jun Wang and Xiangyang Xue},
  booktitle={ECCV},
  year={2014}
}
Fine-grained visual categorization aims at classifying visual data at a subordinate level, e.g., identifying different species of birds. It is a highly challenging topic receiving significant research attention recently. Most existing works focused on the design of more discriminative feature representations to capture the subtle visual differences among categories. Very limited efforts were spent on the design of robust model learning algorithms. In this paper, we treat the training of each… CONTINUE READING
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