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https://github.com/ohhhyeahhh/SiamGAT
Code for the paper "Graph Attention Tracking". (CVPR2021)
https://github.com/ohhhyeahhh/SiamGAT
Last synced: 6 days ago
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Code for the paper "Graph Attention Tracking". (CVPR2021)
- Host: GitHub
- URL: https://github.com/ohhhyeahhh/SiamGAT
- Owner: ohhhyeahhh
- Created: 2020-10-13T08:51:14.000Z (about 4 years ago)
- Default Branch: main
- Last Pushed: 2022-09-04T11:06:08.000Z (about 2 years ago)
- Last Synced: 2024-08-02T06:13:03.647Z (3 months ago)
- Language: Python
- Homepage: https://openaccess.thecvf.com/content/CVPR2021/papers/Guo_Graph_Attention_Tracking_CVPR_2021_paper.pdf
- Size: 371 KB
- Stars: 139
- Watchers: 3
- Forks: 19
- Open Issues: 30
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
- Awesome-Visual-Object-Tracking - [code
README
# SiamGAT
## 1. Environment setup
This code has been tested on Ubuntu 16.04, Python 3.5, Pytorch 1.2.0, CUDA 9.0.
Please install related libraries before running this code:
```bash
pip install -r requirements.txt
```
## 2. Test
Dataset
SiamGAT
SiamGAT*
SiamGAT Model Link
SiamGAT* Model Link
GOT10k
AO
63.1 67.1
Google Driver/
BaiduYun(zktx)
Google Driver/
BaiduYun(d74o)
SR0.5
74.6 78.7
SR0.75
50.4 58.9
TrackingNet
Success
75.3 76.9
Google Driver/
BaiduYun(n2sm)
Google Driver/
BaiduYun(fxo2)
Norm precision
80.7 82.4
Precision
69.8 71.9
LaSOT
Success
53.9 59.5
Google Driver/
BaiduYun(dilp)
Norm precision
63.3 69.0
Precision
53.0 61.2
VOT2020
EAO
- 0.453
-
A
- 0.756
R
- 0.729
OTB100
Success
71.0 71.5
Google Driver/
BaiduYun(w1rs)
Google Driver/
BaiduYun(c6c5)
Precision
91.7 93.0
UAV123
Success
64.6 -
-
Precision
84.3 -
### Prepare testing datasets
Download testing datasets and put them into `test_dataset` directory. Jsons of commonly used datasets can be downloaded from [BaiduYun](https://pan.baidu.com/s/1js0Qhykqqur7_lNRtle1tA#list/path=%2F). If you want to test the tracker on a new dataset, please refer to [pysot-toolkit](https://github.com/StrangerZhang/pysot-toolkit) to set test_dataset.
### Test the tracker
```bash
python testTracker.py \
--config ../experiments/siamgat_googlenet_ct_alldataset/config.yaml \ # siamgat_xx_xx for SiamGAT, siamgat_ct_xx_xx for SiamGAT*
--dataset OTB100 \ # dataset_name: GOT-10k, LaSOT, TrackingNet, OTB100, UAV123
--snapshot snapshot/otb_uav_model.pth # tracker_name
```
The testing result will be saved in the `results/dataset_name/tracker_name` directory.
## 3. Train
### Prepare training datasets
Download the datasets：
* [VID](http://image-net.org/challenges/LSVRC/2017/)
* [YOUTUBEBB](https://pan.baidu.com/s/1gQKmi7o7HCw954JriLXYvg) (code: v7s6)
* [DET](http://image-net.org/challenges/LSVRC/2017/)
* [COCO](http://cocodataset.org)
* [GOT-10K](http://got-10k.aitestunion.com/downloads)
* [LaSOT](https://cis.temple.edu/lasot/)
* [TrackingNet](https://tracking-net.org/#downloads)
**Note:** `training_dataset/dataset_name/readme.md` has listed detailed operations about how to generate training datasets.
### Download pretrained backbones
Download pretrained backbones from [link](https://download.pytorch.org/models/inception_v3_google-1a9a5a14.pth) and put them into `pretrained_models` directory.
### Train a model
To train the SiamGAT model, run `train.py` with the desired configs:
```bash
cd tools
python train.py
--cfg ../experiments/siamgat_googlenet/config.yaml # siamgat_xx_xx for SiamGAT, siamgat_ct_xx_xx for SiamGAT*
```
## 4. Evaluation
We provide tracking results for comparison:
- SiamGAT: [BaiduYun](https://pan.baidu.com/s/1HBE0Kn2ietvQT7NLExAQoA) (extract code: 8nox) or [GoogleDriver](https://drive.google.com/file/d/1xAbTfJNKpGJykdFrTDGtHQtxgKHOhgL7/view?usp=sharing).
- SiamGAT*: [BaiduYun](https://pan.baidu.com/s/1dWhUxsJyE37d8PfOdqFR_g) (extract code: kjym) or [GoogleDriver](https://drive.google.com/file/d/19nzlqz9aCswQwnnvc9AS7btAg_uLCTYI/view?usp=sharing).
If you want to evaluate the tracker on OTB100, UAV123 and LaSOT, please put those results into `results` directory and then run `eval.py` .
Evaluate GOT-10k on [Server](http://got-10k.aitestunion.com/). Evaluate TrackingNet on [Server](https://tracking-net.org/).
```
python eval.py \
--tracker_path ./results \ # result path
--dataset OTB100 \ # dataset_name
--tracker_prefix 'otb_uav_model' # tracker_name
```
## 5. Acknowledgement
The code is implemented based on [pysot](https://github.com/STVIR/pysot) and [SiamCAR](https://github.com/ohhhyeahhh/SiamCAR). We would like to express our sincere thanks to the contributors.
## 6. Cite
If you use SiamGAT 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_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}
}
> @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}
}