by Xiaoping Wang.
Python (PyTorch) implementation of VITAL tracker. VITAL is a great tracker invented by Song, Yibing and Ma, Chao and et al. This implementation is based on py-MDNet, it is implemented by Hyeonseob Nam and Bohyung Han. Thanks to all of them.
If you want this code for personal use, 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}
}
@inproceedings{song-cvpr18-VITAL,
author = {Song, Yibing and Ma, Chao and Wu, Xiaohe and Gong, Lijun and Bao, Linchao and Zuo, Wangmeng and Shen, Chunhua and Lau, Rynson and Yang, Ming-Hsuan},
title = {VITAL: VIsual Tracking via Adversarial Learning},
booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
year = {2018},
}
@inproceedings{xpwang-VITAL-PyTorch,
author = {Xiaoping Wang},
title = {VITAL: VIsual Tracking via Adversarial Learning},
booktitle = {VITAL tracker implemented by PyTorch},
month = {March},
year = {2019},
}
- python 3.6+
- opencv 3.0+
- PyTorch 1.0+ and its dependencies
python tracking/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 tracking/run_tracker.py -s [seq name]
python tracking/run_tracker.py -j [json path]
- Download VGG-M (matconvnet model) and save as "models/imagenet-vgg-m.mat"
- Pretraining on VOT-OTB
- Download VOT datasets into "datasets/VOT/vot201x"
python pretrain/prepro_vot.py python pretrain/train_mdnet.py -d vot
- Pretraining on ImageNet-VID
- Download ImageNet-VID dataset into "datasets/ILSVRC"
python pretrain/prepro_imagenet.py python pretrain/train_mdnet.py -d imagenet