91 citations · 215 across the 16 of their papers we have counts for
7 papers · 1 filter
Active Learning for Deep Visual Tracking
Di Yuan, Xiaojun Chang, Yi Yang +3
Convolutional neural networks (CNNs) have been successfully applied to the single target tracking task in recent years. Generally, training a deep CNN model requires numerous label…
SiamCorners: Siamese Corner Networks for Visual Tracking
Kai Yang, Zhenyu He, Wenjie Pei +4
The current Siamese network based on region proposal network (RPN) has attracted great attention in visual tracking due to its excellent accuracy and high efficiency. However, the…
LSOTB-TIR:A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
Qiao Liu, Xin Li, Zhenyu He +8
In this paper, we present a Large-Scale and high-diversity general Thermal InfraRed (TIR) Object Tracking Benchmark, called LSOTBTIR, which consists of an evaluation dataset and a…
Accurate Bounding-box Regression with Distance-IoU Loss for Visual Tracking
Di Yuan, Xiu Shu, Nana Fan +3
Most existing trackers are based on using a classifier and multi-scale estimation to estimate the target state. Consequently, and as expected, trackers have become more stable whil…
Multi-Task Driven Feature Models for Thermal Infrared Tracking
Qiao Liu, Xin Li, Zhenyu He +4
Existing deep Thermal InfraRed (TIR) trackers usually use the feature models of RGB trackers for representation. However, these feature models learned on RGB images are neither eff…
Learning Deep Multi-Level Similarity for Thermal Infrared Object Tracking
Qiao Liu, Xin Li, Zhenyu He +3
Existing deep Thermal InfraRed (TIR) trackers only use semantic features to describe the TIR object, which lack the sufficient discriminative capacity for handling distractors. Thi…
Particle filter re-detection for visual tracking via correlation filters
Di Yuan, Xiaohuan Lu, Donghao Li +2
Most of the correlation filter based tracking algorithms can achieve good performance and maintain fast computational speed. However, in some complicated tracking scenes, there is…