Code release for The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification (TIP 2020) DOI

• 2020年09月14日 update the code: CUB-200-2011_ResNet18.py Training with ResNet18 (TRAINED FROM SCRATCH).
• 2020年04月19日 add the hyper-parameter fine-tune results.
• 2020年04月18日 clean the code for better understanding.

• python 3.6
• PyTorch 1.2.0
• torchvision

• Download datasets
• Train: python CUB-200-2011.py, the alpha and beta are the hyper-parameters of the MC-Loss
• Description : PyTorch CUB-200-2011 Training with VGG16 (TRAINED FROM SCRATCH).

Loss = ce_loss + alpha_1 * L_dis + beta_1 * L_div
Hyper-parameter_1 Hyper-parameter_2 The figure is plot by NNI.

Other unofficial implements can be found in the following:

• Kurumi233: This repo integrate the MC-Loss into a class. code
• darcula1993: This repo implement the tf version of the MC-Loss. code
• Holocron: Implementations of recent Deep Learning tricks in Computer Vision, easily paired up with your favorite framework and model zoo. code

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

@ARTICLE{9005389, 
author={D. {Chang} and Y. {Ding} and J. {Xie} and A. K. {Bhunia} and X. {Li} and Z. {Ma} and M. {Wu} and J. {Guo} and Y. {Song}}, 
journal={IEEE Transactions on Image Processing}, 
title={The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification}, 
year={2020}, volume={29}, number={}, pages={4683-4695}, 
doi={10.1109/TIP.2020.2973812}, 
ISSN={1941-0042}, 
month={},} 

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

• changdongliang@bupt.edu.cn
• mazhanyu@bupt.edu.cn