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@ -6,7 +6,7 @@ Speical thanks to [Yuanzhi Liang](https://github.com/akira-l) for code refactori
## Introduction ## Introduction
This project is a DCL pytorch implementation of [*Destruction and Construction Learning for Fine-grained Image Recognition*](http://openaccess.thecvf.com/content_CVPR_2019/html/Chen_Destruction_and_Construction_Learning_for_Fine-Grained_Image_Recognition_CVPR_2019_paper.html) accepted by CVPR2019. This project is a DCL pytorch implementation of [*Destruction and Construction Learning for Fine-grained Image Recognition*](http://openaccess.thecvf.com/content_CVPR_2019/html/Chen_Destruction_and_Construction_Learning_for_Fine-Grained_Image_Recognition_CVPR_2019_paper.html), CVPR2019.
## Requirements ## Requirements
@ -106,3 +106,17 @@ For training FGVC datasets from trained checkpoint
--detail training_descibe4checkpoint --size 512 \ --detail training_descibe4checkpoint --size 512 \
--crop 448 --cls_2 --swap_num 7 7 --crop 448 --cls_2 --swap_num 7 7
``` ```
## Citation
Please cite our CVPR19 paper if you use DCL in your work:
```
@InProceedings{Chen_2019_CVPR,
author = {Chen, Yue and Bai, Yalong and Zhang, Wei and Mei, Tao},
title = {Destruction and Construction Learning for Fine-Grained Image Recognition},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}
```