- Python3
- PyTorch ==1.6.0 (with suitable CUDA and CuDNN version)
- torchvision == 0.7.0
- Numpy
- argparse
- transformers == 4.6.1
You can run "cityscapes/run.sh" to train and evaluate on the CityScapes dataset.
You can run "nyu/run.sh" to train and evaluate on the NYUv2 dataset.
You can run "pascal/run.sh" to train and evaluate on the PASCAL-Context dataset.
You can run "taskonomy/run.sh" to train and evaluate on the Taskonomy dataset.
If you use this code for your research, please consider citing:
@article{guo2021safe,
title={Safe Multi-Task Learning},
author={Guo, Pengxin and Ye, Feiyang and Zhang, Yu},
journal={arXiv preprint arXiv:2111.10601},
year={2021}
}
If you have any problem about our code, feel free to contact 12032913@mail.sustech.edu.cn.