This code has been tested on Ubuntu 16.04, Python 3.6, Pytorch 0.4.1/1.2.0, CUDA 9.0. Please install related libraries before running this code:

pip install -r requirements.txt

Download the pretrained model:
general_model code: lw7w
got10k_model code: p4zx
LaSOT_model code: 6wer
(The model in google Driver) and put them into tools/snapshot directory.

Download testing datasets and put them into test_dataset directory. Jsons of commonly used datasets can be downloaded from BaiduYun or Google driver. If you want to test the tracker on a new dataset, please refer to pysot-toolkit to set test_dataset.

python test.py                                \
	--dataset UAV123                      \ # dataset_name
	--snapshot snapshot/general_model.pth  # tracker_name

The testing result will be saved in the results/dataset_name/tracker_name directory.

Download the datasets：

• VID
• YOUTUBEBB (code: v7s6)
• DET
• COCO
• GOT-10K
• LaSOT

Note: train_dataset/dataset_name/readme.md has listed detailed operations about how to generate training datasets.

Download pretrained backbones from google driver or BaiduYun (code: 7n7d) and put them into pretrained_models directory.

To train the SiamCAR model, run train.py with the desired configs:

cd tools
python train.py

We provide the tracking results (code: 4er6) (results in google driver )of GOT10K, LaSOT, OTB, UAV, VOT2018 and TrackingNet. If you want to evaluate the tracker, please put those results into results directory.

python eval.py 	                          \
	--tracker_path ./results          \ # result path
	--dataset UAV123                  \ # dataset_name
	--tracker_prefix 'general_model'   # tracker_name

The code is implemented based on pysot. We would like to express our sincere thanks to the contributors.

If you use SiamCAR in your work please cite our papers:

@article{cui2022joint,
title={Joint Classification and Regression for Visual Tracking with Fully Convolutional Siamese Networks},
author={Cui, Ying and Guo, Dongyan and Shao, Yanyan and Wang, Zhenhua and Shen, Chunhua and Zhang, Liyan and Chen, Shengyong},
journal={International Journal of Computer Vision},
year={2022},
publisher={Springer},
doi = {10.1007/s11263-021-01559-4}
}

@InProceedings{Guo_2020_CVPR,
author = {Guo, Dongyan and Wang, Jun and Cui, Ying and Wang, Zhenhua and Chen, Shengyong},
title = {SiamCAR: Siamese Fully Convolutional Classification and Regression for Visual Tracking},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}
}

@InProceedings{Guo_2021_CVPR,
author = {Guo, Dongyan and Shao, Yanyan and Cui, Ying and Wang, Zhenhua and Zhang, Liyan and Shen, Chunhua},
title = {Graph Attention Tracking},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2021}
}