Relational Surrogate Loss Learning (ReLoss)
Official implementation for paper “Relational Surrogate Loss Learning” in International Conference on Learning Representations (ICLR) 2022.
By Tao Huang, Zekang Li, Hua Lu, Yong Shan, Shusheng Yang, Yang Feng, Fei Wang, Shan You, Chang Xu.
Usage
Install ReLoss
pip install git+https://github.com/hunto/ReLoss.git
Or install for development:
git clone https://github.com/hunto/ReLoss
cd ReLoss
pip install -e .
Training with ReLoss
All the inputs and outputs of ReLoss are the same as the original loss.
- classification
from reloss.cls import ReLoss loss_fn = ReLoss()
- human pose estimation
from reloss.pose import ReLoss loss_fn = ReLoss(heatmap_size=(64, 48))
Citation
@inproceedings{
huang2022relational,
title={Relational Surrogate Loss Learning},
author={Tao Huang and Zekang Li and Hua Lu and Yong Shan and Shusheng Yang and Yang Feng and Fei Wang and Shan You and Chang Xu},
booktitle={International Conference on Learning Representations},
year={2022},
url={https://openreview.net/forum?id=dZPgfwaTaXv}
}
