no code implementations • 16 Sep 2023 • Zhiruo Zhou, Suya You, C. -C. Jay Kuo
The labeling cost and the huge computational complexity hinder their applications on edge devices.
no code implementations • 15 Jul 2022 • Zhiruo Zhou, Hongyu Fu, Suya You, C. -C. Jay Kuo
Supervised and unsupervised deep trackers that rely on deep learning technologies are popular in recent years.
no code implementations • 15 Nov 2021 • Zhiruo Zhou, Hongyu Fu, Suya You, C. -C. Jay Kuo
Based on the experimental results, we compare pros and cons of supervised and unsupervised trackers and provide a new perspective to understand the performance gap between supervised and unsupervised methods, which is the third contribution of this work.
no code implementations • 5 Oct 2021 • Zhiruo Zhou, Hongyu Fu, Suya You, Christoph C. Borel-Donohue, C. -C. Jay Kuo
An unsupervised online object tracking method that exploits both foreground and background correlations is proposed and named UHP-SOT (Unsupervised High-Performance Single Object Tracker) in this work.
no code implementations • 9 Sep 2020 • Ruiyuan Lin, Zhiruo Zhou, Suya You, Raghuveer Rao, C. -C. Jay Kuo
Besides input layer $l_{in}$ and output layer $l_{out}$, the MLP of interest consists of two intermediate layers, $l_1$ and $l_2$.