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py-VITAL

by Xiaoping Wang.

Introduction

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},
}  

Prerequisites

Usage

Tracking

 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]

Pretraining

  • 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