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
Dataset | SiamCAR | |
OTB100 | Success | 70.0 |
Precision | 91.4 | |
UAV123 | Success | 64.0 |
Precision | 83.9 | |
LaSOT | Success | 51.6 |
Norm precision | 61.0 | |
Precision | 52.4 | |
GOT10k | AO | 58.1 |
SR0.5 | 68.3 | |
SR0.75 | 44.1 | |
VOT2018 | EAO | 42.3 |
Robustness | 19.7 | |
Accuracy | 57.4 | |
VOT2020 | EAO | 27.3 |
Robustness | 73.2 | |
Accuracy | 44.9 | |
TrackingNet | Success | 74.0 |
Norm precision | 80.4 | |
Precision | 68.4 |
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:
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}
}