SiamCorners

This is an official implemention for “SiamCorners: Siamese Corner Networks for VisualTracking”. The code are available here now.

The overview of our SiamCorners architecture, which includes the Siamese feature extractor followed by the top-left corner and bottom-right corner branches in parallel.

Dependencies

• Python 3.7
• PyTorch 1.0.0
• numpy
• CUDA 10
• skimage
• matplotlib
• GCC 4.9.2 or above

Prepare training dataset

Prepare training dataset, detailed preparations are listed in training_dataset directory.

• VID
• YOUTUBEBB (BaiduYun, extract code: h964.)
• DET
• COCO
• LaSOT
• GOT10k

Compiling Corner Pooling Layers

Compile the C++ implementation of the corner pooling layers. (GCC4.9.2 or above is required.)

cd <SiamCorners dir>/pysot/models/corners/py_utils/_cpools
python setup.py install --user

Compiling NMS

Compile the NMS code which are originally from Faster R-CNN and Soft-NMS.

cd <SiamCorners dir>/pysot/tracker/external
make

Training:

CUDA_VISIBLE_DEVICES=0,1
python -m torch.distributed.launch \
    --nproc_per_node=2 \
    --master_port=2333 \
    ../../tools/train.py --cfg config.yaml

Testing:

python ../tools/test.py 

Citation

If you're using this code in a publication, please cite our paper.

@InProceedings{SiamCorners,
author = {Kai Yang, Zhenyu He, Wenjie Pei, Zikun Zhou, Xin Li, Di Yuan and Haijun Zhang},
title = {SiamCorners: Siamese Corner Networks for Visual Tracking},
booktitle = {IEEE Transactions on Multimedia},
month = {April},
year = {2021}
}

Acknowledgment

Our anchor-free tracker is based on PySot and CornerNet. We sincerely thank the authors Bo Li and Hei Law for providing these great works.

Contact

If you have any questions, please feel free to contact yangkaik88@163.com