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 theMC-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={},}
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