Official Implementation of our paper:
- Tianshui Chen, Weihang Wang, Tao Pu, Jinghui Qin, Zhijing Yang, Jie Liu, Liang Lin.
DCLR: Dynamic Correlation Learning and Regularization for Multi-Label Confidence Calibration.
IEEE Transactions on Image Processing, 2024.
We run the code with torch version: 1.11.0, python version: 3.9.7
The detailed requirements is in requirements.txt
. Please use the
pip install -r requirements.txt
pip install command to install it.
Our method works for COCO and VG datasets, please modify your dataset path
under config/dataset
.
If you want to use your own dataset, you can configure it by copying the dataset writeup under the config/dataset
.
Afterwards, specify your dataset on the command line using the -dataset
parameter. See the config
and scripts
folders for details on how to configure it.
# SSGRL module on COCO dataset:
bash scripts/SSGRL_COCO_Calibration.sh
# MLGCN module on COCO dataset:
bash scripts/MLGCN_COCO_Calibration.sh
# CTran module on COCO dataset:
bash scriptsMLGCN_COCO_Calibration.sh
@article{chen2024dynamic,
title={Dynamic Correlation Learning and Regularization for Multi-Label Confidence Calibration},
author={Chen, Tianshui and Wang, Weihang and Pu, Tao and Qin, Jinghui and Yang, Zhijing and Liu, Jie and Lin, Liang},
journal={IEEE Transactions on Image Processing},
year={2024}
}
If you have any questions for our paper or codes, please send an email to [email protected] or [email protected].