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Fine-Grained-or-Not

Code release for Your “Flamingo” is My “Bird”: Fine-Grained, or Not (CVPR 2021 Oral) DOI

Changelog

  • 2021/03/05 upload the code.

Requirements

  • python 3.6
  • PyTorch 1.2.0
  • torchvision

Data

  • Download datasets
  • Extract them to data/cars/, data/birds/ and data/airs/, respectively.
  • Split the dataset into train and test folder, the index of each class should follow the Birds.xls, Air.xls, and Cars.xls
  • e.g., CUB-200-2011 dataset
  -/birds/train
	         └─── 001.Black_footed_Albatross
	                   └─── Black_Footed_Albatross_0001_796111.jpg
	                   └─── ...
	         └─── 002.Laysan_Albatross
	         └─── 003.Sooty_Albatross
	         └─── ...
   -/birds/test	
             └─── ...

Training

  • python Birds_ours_resnet.py or python Air_ours_resnet.py or python Cars_ours_resnet.py

Citation

If you find this paper useful in your research, please consider citing:

@InProceedings{Chang2021Labrador,
  title={Your “Flamingo” is My “Bird”: Fine-Grained, or Not},
  author={Chang, Dongliang and Pang, Kaiyue and Zheng, Yixiao and Ma, Zhanyu and Song, Yi-Zhe and Guo, Jun},
  booktitle = {Computer Vision and Pattern Recognition},
  year={2021}
}

Contact

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