Flexible Dual-Branch Siamese Network: Learning Location Quality Estimation and Regression Distribution for Visual Tracking

IEEE Transactions on Computational Social Systems

1.result

Dataset		SiamFDB
OTB100	Success	70.4
	Precision	91.9
UAV123	Success	64.9
	Precision	84.0
LaSOT	Success	52.7
	Norm precision	60.9
	Precision	54.0
GOT10k	AO	63.5
	SR0.5	73.8
	SR0.75	51.0
VOT2019	EAO	31.7
	Accuracy	60.3
	Robustness	42.6

2. Environment setup

This code has been tested on Ubuntu 18.04, Python 3.7, Pytorch 1.7.1, CUDA 11. Please install related libraries before running this code:

pip install -r requirements.txt

Download the pretrained model:

The model has been trained for testing and validation.

model code: xyqt

Download testing datasets and put them into test_dataset directory. If you want to test the tracker on a new dataset, please refer to pysot-toolkit to set test_dataset.

Download pretrained backbones

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

3.train

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

For OTB and VOT Benchmark.

cd /path/to/SiamFDB
export PYTHONPATH=./:$PYTHONPATH
python tools/train.py --cfg ./experiments/SiamFDB_r50/configOTBVOT.yaml

For UAV Benchmark

cd /path/to/SiamFDB
export PYTHONPATH=./:$PYTHONPATH
python tools/train.py --cfg ./experiments/SiamFDB_r50/config.yaml

For GOT10k Benchmark

cd /path/to/SiamFDB
export PYTHONPATH=./:$PYTHONPATH
python tools/train.py --cfg ./experiments/SiamFDB_r50_got10k/config.yaml

For LaSOT Benchmark

cd /path/to/SiamFDB
export PYTHONPATH=./:$PYTHONPATH
python tools/train.py --cfg ./experiments/SiamFDB_r50_lasot/config.yaml

4.test

cd /path/to/SiamFDB
export PYTHONPATH=./:$PYTHONPATH
python tools/test.py --config ./experiments/SiamFDB_r50/config.yaml --dataset UAV123 --snapshot ./models/UAV123.pth

5.eval

please refer to pysot-toolkit

6.tune

cd /path/to/SiamFDB
export PYTHONPATH=./:$PYTHONPATH
python tools/tune.py                                \
	--dataset_root  /path/to/dataset/root            \ # dataset path
	--dataset UAV123                                \ # dataset name(OTB100, GOT10k, LaSOT, UAV123, VOT2016, VOT2018, VOT2019)
	--snapshot ./models/UAV123.pth           \ # tracker_name
	--config ./experiments/SiamFDB_r50/config.yaml   \ # config file

7.Cite

If you use SiamFDB in your work please cite our paper:

@ARTICLE{10034430,
author={Hu, Shuo and Zhou, Sien and Lu, Jinbo and Yu, Hui},
journal={IEEE Transactions on Computational Social Systems},
title={Flexible Dual-Branch Siamese Network: Learning Location Quality Estimation and Regression Distribution for Visual Tracking},
year={2023},
volume={},
number={},
pages={1-9},
doi={10.1109/TCSS.2023.3235649}
}