Skip navigation
Skip navigation

Robust Tracking using Manifold Convolutional Neural Networks with Laplacian Regularization

Hu, Hongwei; Ma, Bo; Shen, Jianbing; Hanqiu, Sun; Shao, Ling; Porikli, Fatih


In visual tracking, usually only a small number of samples are labeled, and most existing deep learning based trackers ignore abundant unlabeled samples that could provide additional information for deep trackers to boost their tracking performance. An intuitive way to explain unlabeled data is to incorporate manifold regularization into the common classification loss functions, but the high computational cost may prohibit those deep trackers from practical applications. To overcome this issue,...[Show more]

CollectionsANU Research Publications
Date published: 2018
Type: Journal article
Source: IEEE Transactions on Multimedia
DOI: 10.1109/TMM.2018.2859831
Access Rights: Open Access


File Description SizeFormat Image
01_Hu_Robust_Tracking_using_Manifold_2018.pdf4.63 MBAdobe PDFThumbnail

Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  17 November 2022/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator