RPN2T

Robust Tracking Using Region Proposal Networks
https://arxiv.org/pdf/1705.10447.pdf

Introduction

RPN2T tracker achieved state-of-the-art results on several large scale benchmarks including OTB50, OTB100 and VOT2016.

Detailed description of the system is provided by our paper(https://arxiv.org/pdf/1705.10447.pdf).

This software is implemented using Caffe and part of Faster_rcnn.

Citation

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

@article{  
  Jimmy2017RPN2T,  
  title={Robust Tracking Using Region Proposal Networks},  
  author={Ren, Jimmy and Yu, Zhiyang and Liu, Jianbo and Zhang, Rui and Sun, Wenxiu and Pang, Jiahao and Chen, Xiaohao and Yan, Qiong},  
  journal={arXiv preprint arXiv:1705.10447},  
  year={2017}  
}

System Requirements

This code is tested on 64 bit Linux (Ubuntu 14.04 LTS).

Prerequisites

0. MATLAB (tested with R2014b)
1. Caffe (included in this repository external/_caffe/)
2. For GPU support, a GPU, CUDA toolkit and cuDNN will be needed. We have tested in GTX TitanX(MAXWELL) with CUDA7.5+cuDNNv5 and GTX 1080 with CUDA8.0+cuDNNv5.1.

Installation

Compile Caffe according to the installation guideline.

cd $(RPN2T_ROOT)
cd external/_caffe
# Adjust Makefile.config (For example, the path of MATLAB.)
make all -j8
make matcaffe

Online Tracking using RPN2T

Demo

Run 'tracking/demo_tracking.m'.