Progressive Multi-Granularity Training

Code release for Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches (ECCV2020)

Requirement

python 3.6

PyTorch >= 1.3.1

torchvision >= 0.4.2

Training

1. Download datatsets for FGVC (e.g. CUB-200-2011, Standford Cars, FGVC-Aircraft, etc) and organize the structure as follows:

   dataset
   ├── train
   │   ├── class_001
   |   |      ├── 1.jpg
   |   |      ├── 2.jpg
   |   |      └── ...
   │   ├── class_002
   |   |      ├── 1.jpg
   |   |      ├── 2.jpg
   |   |      └── ...
   │   └── ...
   └── test
   ├── class_001
   |      ├── 1.jpg
   |      ├── 2.jpg
   |      └── ...
   ├── class_002
   |      ├── 1.jpg
   |      ├── 2.jpg
   |      └── ...
   └── ...

2. Train from scratch with train.py.

Citation

Please cite our paper if you use PMG in your work.

@InProceedings{du2020fine,
  title={Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches},
  author={Du, Ruoyi and Chang, Dongliang and Bhunia, Ayan Kumar and Xie, Jiyang and Song, Yi-Zhe and Ma, Zhanyu and Guo, Jun},
  booktitle = {European Conference on Computer Vision},
  year={2020}
}

Contact

Thanks for your attention! If you have any suggestion or question, you can leave a message here or contact us directly:

• mazhanyu@bupt.edu.cn
• beiyoudry@bupt.edu.cn