The Devil is in the Channels: Mutual-Channel Loss for Fine-Grained Image Classification

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

Changelog

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

Dataset

CUB-200-2011

Requirements

• python 3.6
• PyTorch 1.2.0
• torchvision

Training

• 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).

Hyper-parameter

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

Other versions

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

Citation

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={},} 

Contact

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