Amgao/RLS-RTMDNet

Code and raw result files of our CVPR2020 oral paper "Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking""

RLS-RTMDNet

Code and raw result files of our CVPR2020 oral paper "Recursive Least-Squares Estimator-Aided Online Learning for Visual Tracking"

Created by Jin Gao

Introduction

RLS-RTMDNet is dedicated to improving online tracking part of RT-MDNet (project page and paper) based on our proposed recursive least-squares estimator-aided online learning method.

Citation

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

@InProceedings{Gao_2020_CVPR,
author = {Gao, Jin and Hu, Weiming and Lu, Yan},
	title = {Recursive Least-squares Estimator-aided Online Learning for Visual Tracking},
	booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	month = {June},
	year = {2020}
}

System Requirements

This code is tested on 64 bit Linux (Ubuntu 16.04 LTS) with the following Anaconda environment:

• PyTorch (= 1.2.0)
• Python (= 3.7.4)

Online Tracking

Pretrained Model

• The off-the-shelf pretrained model in RT-MDNet is used for our testing: RT-MDNet-ImageNet-pretrained.

Demo

• 'Run.py' for OTB and UAV123
• 'python_RLS_RTMDNet.py' for VOT16/17.