research-article

LSOTB-TIR: A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark

Authors:

Feng ZhengAuthors Info & Claims

MM '20: Proceedings of the 28th ACM International Conference on Multimedia

Pages 3847 - 3856

https://doi.org/10.1145/3394171.3413922

Published: 12 October 2020 Publication History

Abstract

In this paper, we present a Large-Scale and high-diversity general Thermal InfraRed (TIR) Object Tracking Benchmark, called LSOTB-TIR, which consists of an evaluation dataset and a training dataset with a total of 1,400 TIR sequences and more than 600K frames. We annotate the bounding box of objects in every frame of all sequences and generate over 730K bounding boxes in total. To the best of our knowledge, LSOTB-TIR is the largest and most diverse TIR object tracking benchmark to date. To evaluate a tracker on different attributes, we define 4 scenario attributes and 12 challenge attributes in the evaluation dataset. By releasing LSOTB-TIR, we encourage the community to develop deep learning based TIR trackers and evaluate them fairly and comprehensively. We evaluate and analyze more than 30 trackers on LSOTB-TIR to provide a series of baselines, and the results show that deep trackers achieve promising performance. Furthermore, we re-train several representative deep trackers on LSOTB-TIR, and their results demonstrate that the proposed training dataset significantly improves the performance of deep TIR trackers. Codes and dataset are available at https://github.com/QiaoLiuHit/LSOTB-TIR.

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Cited By

Zhang LWang LWu YChen MZheng DCao LZeng BCai Y(2025)UniRTL: A universal RGBT and low-light benchmark for object trackingPattern Recognition10.1016/j.patcog.2024.110984158(110984)Online publication date: Feb-2025
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Shu XHuang FQiu ZZhang XYuan D(2024)Learning Unsupervised Cross-Domain Model for TIR Target TrackingMathematics10.3390/math1218288212:18(2882)Online publication date: 15-Sep-2024
https://doi.org/10.3390/math12182882
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Index Terms

LSOTB-TIR: A Large-Scale High-Diversity Thermal Infrared Object Tracking Benchmark
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Tracking
      2. Computer vision representations
        Image representations

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Published In

cover image ACM Conferences

MM '20: Proceedings of the 28th ACM International Conference on Multimedia

October 2020

4889 pages

ISBN:9781450379885

DOI:10.1145/3394171

General Chairs:
Chang Wen Chen
Chinese University of Hong Kong, Shenzhen, China
,
Rita Cucchiara
UNIMORE, Italy
,
Xian-Sheng Hua
Alibaba Group, China
,
Program Chairs:
Guo-Jun Qi
Futurewei Technologies, USA
,
Elisa Ricci
UNITN & Fondazione Bruno Kessler, Italy
,
Zhengyou Zhang
Tencent, China
,
Roger Zimmermann
National University of Singapore, Singapore

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Published: 12 October 2020

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MM '20: The 28th ACM International Conference on Multimedia

October 12 - 16, 2020

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Cited By

Zhang LWang LWu YChen MZheng DCao LZeng BCai Y(2025)UniRTL: A universal RGBT and low-light benchmark for object trackingPattern Recognition10.1016/j.patcog.2024.110984158(110984)Online publication date: Feb-2025
https://doi.org/10.1016/j.patcog.2024.110984
DAI Yuhang 代LIU Qiao 刘YUAN Di 袁FAN Nana 范LIU Yunpeng 刘(2024)低秩自适应微调的一阶段红外目标跟踪Infrared and Laser Engineering10.3788/IRLA2024019953:8(20240199)Online publication date: 2024
https://doi.org/10.3788/IRLA20240199
Shu XHuang FQiu ZZhang XYuan D(2024)Learning Unsupervised Cross-Domain Model for TIR Target TrackingMathematics10.3390/math1218288212:18(2882)Online publication date: 15-Sep-2024
https://doi.org/10.3390/math12182882
Wang BLi QMao QWang JChen CShangguan AZhang H(2024)A Survey on Vision-Based Anti Unmanned Aerial Vehicles MethodsDrones10.3390/drones80905188:9(518)Online publication date: 23-Sep-2024
https://doi.org/10.3390/drones8090518
Wu JZhou XLi XLiu HQi MHong R(2024)Asymmetric Deformable Spatio-temporal Framework for Infrared Object TrackingACM Transactions on Multimedia Computing, Communications, and Applications10.1145/367888220:10(1-24)Online publication date: 19-Jul-2024
https://dl.acm.org/doi/10.1145/3678882
Huang BLi JChen JWang GZhao JXu T(2024)Anti-UAV410: A Thermal Infrared Benchmark and Customized Scheme for Tracking Drones in the WildIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.333533846:5(2852-2865)Online publication date: May-2024
https://doi.org/10.1109/TPAMI.2023.3335338
Liu QLi XYuan DYang CChang XHe Z(2024)LSOTB-TIR: A Large-Scale High-Diversity Thermal Infrared Single Object Tracking BenchmarkIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2023.323689535:7(9844-9857)Online publication date: Jul-2024
https://doi.org/10.1109/TNNLS.2023.3236895
Yuan DLiao DHuang FQiu ZShu XTian CLiu Q(2024)Hierarchical Attention Siamese Network for Thermal Infrared Target TrackingIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2024.346297373(1-11)Online publication date: 2024
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Yuan DZhang HShu XLiu QChang XHe ZShi G(2024)Thermal Infrared Target Tracking: A Comprehensive ReviewIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2023.333870173(1-19)Online publication date: 2024
https://doi.org/10.1109/TIM.2023.3338701
Fang HWu CWang XZhou FChang YYan L(2024)Online Infrared UAV Target Tracking With Enhanced Context-Awareness and Pixel-Wise Attention ModulationIEEE Transactions on Geoscience and Remote Sensing10.1109/TGRS.2024.343210862(1-17)Online publication date: 2024
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