If you fail to install and run this tracker, please email me ([email protected])
This repository includes tensorflow code of MBMD (MobileNet-based tracking by detection algorithm) for VOT2018 Long-Term Challenge.
The corresponding arxiv paper has been drafted on Arxiv.
Learning regression and verification networks for long-term visual tracking.
Yunhua Zhang, Dong Wang, Lijun Wang, Jinqing Qi, Huchuan Lu
python 2.7
ubuntu 14.04
cuda-8.0
cudnn-6.0.21
Tensorflow-1.3-gpu
NVIDIA TITAN X GPU
The bounding box regression's architecture is MobileNet, and the verifier's architecture is VGGM.
The pre-trained model can be downloaded at https://drive.google.com/open?id=1g3aMRi6CWK88FOEYoQjqs61fY6QvGW1Z.
Then you should copy the two files to the folder of our code.
The interface for integrating the tracker into the vot evaluation tool kit is implemented in the module python_long_MBMD.py. The script tracker_MBMD.m is needed to be copied to vot-tookit.
If you want to run this code on CPU, you need to just set os.environ ["CUDA_VISIBLE_DEVICES"]="" in the begin of python_long_MBMD.py
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