Awesome
Fine-Grained-or-Not
Code release for Your “Flamingo” is My “Bird”: Fine-Grained, or Not (CVPR 2021 Oral) DOI
<!-- ![Labrador](./labrador.jpg) -->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/
anddata/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
orpython Air_ours_resnet.py
orpython 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
Thanks for your attention! If you have any suggestion or question, you can leave a message here or contact us directly: