168 citations · 323 across the 9 of their papers we have counts for
9 papers · 1 filter
Pose-Aided Video-based Person Re-Identification via Recurrent Graph Convolutional Network
Honghu Pan, Qiao Liu, Yongyong Chen +4
Existing methods for video-based person re-identification (ReID) mainly learn the appearance feature of a given pedestrian via a feature extractor and a feature aggregator. However…
An Informative Tracking Benchmark
Xin Li, Qiao Liu, Wenjie Pei +4
Along with the rapid progress of visual tracking, existing benchmarks become less informative due to redundancy of samples and weak discrimination between current trackers, making…
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…
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…
PTB-TIR: A Thermal Infrared Pedestrian Tracking Benchmark
Qiao Liu, Zhenyu He, Xin Li +1
Thermal infrared (TIR) pedestrian tracking is one of the important components among numerous applications of computer vision, which has a major advantage: it can track pedestrians…
Hierarchical Spatial-aware Siamese Network for Thermal Infrared Object Tracking
Xin Li, Qiao Liu, Nana Fan +2
Most thermal infrared (TIR) tracking methods are discriminative, treating the tracking problem as a classification task. However, the objective of the classifier (label prediction)…