├── data/
│   ├── Cityscapes/     
|   |   ├── gtFine/
|   |   ├── leftImg8bit/
│   ├── GTA5/
|   |   ├── images/
|   |   ├── labels/
│   ├── SYNTHIA/ 
|   |   ├── RAND_CITYSCAPES/
│   └── 			
└── model/
│   ├── DeepLab_resnet_pretrained.pth
...

CUDA_VISIBLE_DEVICES=0 python CLAN_train.py --snapshot-dir ./snapshots/GTA2Cityscapes

CUDA_VISIBLE_DEVICES=0 python CLAN_evaluate.py --restore-from  ./snapshots/GTA2Cityscapes/GTA5_100000.pth --save ./result/GTA2Cityscapes_100000

python CLAN_iou.py ./data/Cityscapes/gtFine/val result/GTA2Cityscapes_100000

CUDA_VISIBLE_DEVICES=0 python CLAN_evaluate_bulk.py
python CLAN_iou_bulk.py

@article{luo2021category,
  title={Category-Level Adversarial Adaptation for Semantic Segmentation using Purified Features},
  author={Luo, Yawei and Liu, Ping and Zheng, Liang and Guan, Tao and Yu, Junqing and Yang, Yi},
  journal={IEEE Transactions on Pattern Analysis \& Machine Intelligence (TPAMI)},
  year={2021},
}
@inproceedings{luo2019Taking,
title={Taking A Closer Look at Domain Shift: Category-level Adversaries for Semantics Consistent Domain Adaptation},
author={Luo, Yawei and Zheng, Liang and Guan, Tao and Yu, Junqing and Yang, Yi},
booktitle={The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2019}
}