by Hyeonseob Nam and Bohyung Han at POSTECH
Python (PyTorch) implementation of MDNet tracker, which is ~2x faster than the original matlab implementation.
If you're using this code for your research, please cite:
@InProceedings{nam2016mdnet,
author = {Nam, Hyeonseob and Han, Bohyung},
title = {Learning Multi-Domain Convolutional Neural Networks for Visual Tracking},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2016}
}
- python 2.7 or Python 3.5+
- PyTorch and its dependencies
cd tracking
python run_tracker.py -s DragonBaby [-d (display fig)] [-f (save fig)]
- You can provide a sequence configuration in two ways (see tracking/gen_config.py):
python run_tracker.py -s [seq name]
python run_tracker.py -j [json path]
- Download VGG-M (matconvnet model) and save as "models/imagenet-vgg-m.mat"
- Download VOT datasets into "dataset/vot201x"
cd pretrain
python prepro_data.py
python train_mdnet.py