Search Results for author:
Found 5 papers, 0 papers with code
Unsupervised Green Object Tracker (GOT) without Offline Pre-training
The labeling cost and the huge computational complexity hinder their applications on edge devices.
GUSOT: Green and Unsupervised Single Object Tracking for Long Video Sequences
Supervised and unsupervised deep trackers that rely on deep learning technologies are popular in recent years.
Unsupervised Lightweight Single Object Tracking with UHP-SOT++
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.
UHP-SOT: An Unsupervised High-Performance Single Object Tracker
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.
From Two-Class Linear Discriminant Analysis to Interpretable Multilayer Perceptron Design
Besides input layer $l_{in}$ and output layer $l_{out}$, the MLP of interest consists of two intermediate layers, $l_1$ and $l_2$.
