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[202105]长时视觉目标跟踪前沿简介.pdf
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Long-term Visual Tracking:

This page focuses on watching the state-of-the-art performance for the long-term tracking task (if you are interested in the short-term tracking task, please visit here). If you are also interested in some resources on Paper Writting (computer vision), please visit here.

Survey

Benchmark Results:

Benchmark

  • List:

    Datasets #videos #total/min/max/average frames Absent Label
    VOT2019-LT/VOT2020-LT/VOT2021-LT 50 XXXX/XXXX/XXXX/XXXX Yes
    TLP 50 XXXX/XXXX/XXXX/XXXX No
    OxUvA 366 (dev-200/test-166) XXXX/XXXX/XXXX/XXXX Yes
    LaSOT 1,400 (I-all-1,400/II-test-280) 3.52M/1,000/11,397/2,506 Yes
    • UAV-20L has been included in VOT2018-LT/VOT2019-LT/VOT2020-LT.
    • VOT2018-LT is a subset of VOT2019-LT/VOT2020-LT/VOT2021-LT. VOT2019-LT, VOT2020-LT and VOT2021-LT are same.

  • VOT: . [Visual Object Tracking Challenge]

  • OxUvA: Jack Valmadre, Luca Bertinetto, João F. Henriques, Ran Tao, Andrea Vedaldi, Arnold Smeulders, Philip Torr, Efstratios Gavves.
    "Long-term Tracking in the Wild: a Benchmark." ECCV (2018). [paper] [project]

  • TLP: Abhinav Moudgil, Vineet Gandhi.
    "Long-term Visual Object Tracking Benchmark." ACCV (2018). [paper] [project]

  • CDTB: Alan Lukežič, Ugur Kart, Jani Käpylä, Ahmed Durmush, Joni-Kristian Kämäräinen, Jiří Matas, Matej Kristan.
    "CDTB: A Color and Depth Visual Object Tracking Dataset and Benchmark." ICCV (2019). [paper] RGB-D Long-term

  • LaSOT: Heng Fan, Liting Lin, Fan Yang, Peng Chu, Ge Deng, Sijia Yu, Hexin Bai, Yong Xu, Chunyuan Liao, Haibin Ling.
    "LaSOT: A High-quality Benchmark for Large-scale Single Object Tracking." CVPR (2019). [paper] [project]
    The LaSOT dataset is not a typical long-term dataset. But it is a good choice for connecting long-term and short-term trackers. Usually, short-term trackers drift very easily in the long-term datasets since they have no re-detection module. Long-term trackers also achieve unsatisfactory performance in the short-term datasets, since the tested sequences are often very short and the evaluation criterion pay less attention to the re-detection capability (especially VOT' EAO). LaSOT is a large-scale, long-frame dataset with precision and succuess criterion. Thus, it is a good choice if you want to fairly compare the performance of long-term and short-term trackers in one figure/table.

  • UAV20L: Matthias Mueller, Neil Smith and Bernard Ghanem.
    "A Benchmark and Simulator for UAV Tracking." ECCV (2016). [paper] [project] [dataset]
    All 20 videos of UAV20L have been included in the VOT2018LT dataset.

Recent Long-term Trackers

  • STARK: Bin Yan, Houwen Peng, Jianlong Fu, Dong Wang, Huchuan Lu.
    "Learning Spatio-Temporal Transformer for Visual Tracking." ICCV, 2021. [Paper] [Code]

  • KeepTrack: Christoph Mayer, Martin Danelljan, Danda Pani Paudel, Luc Van Gool.
    "Learning Target Candidate Association to Keep Track of What Not to Track." ICCV (2021). [Paper] [Project]

  • DMTrack: Zikai Zhang, Bineng Zhong, Shengping Zhang, Zhenjun Tang, Xin Liu, Zhaoxiang Zhang.
    "Distractor-Aware Fast Tracking via Dynamic Convolutions and MOT Philosophy." CVPR (2021). [Paper] [Project]

  • LTMU: Kenan Dai, Yunhua Zhang, Dong Wang, Jianhua Li, Huchuan Lu, Xiaoyun Yang.
    High-Performance Long-Term Tracking with Meta-Updater. CVPR (2020). [Paper] [Code]
    VOT2019-LT Winner🌟, VOT2020-LT Winner🌟
    1. This work is an improved version of the VOT2019-LT winner, [LT_DSE].
    2. The baseline version is the VOT2020-LT winner, [LTMU_B].

  • Siam R-CNN: Paul Voigtlaender, Jonathon Luiten, Philip H.S. Torr, Bastian Leibe.
    "Siam R-CNN: Visual Tracking by Re-Detection." CVPR (2020). [Paper] [Code] [Project]

  • TACT: Janghoon Choi, Junseok Kwon, Kyoung Mu Lee.
    "Visual Tracking by TridentAlign and Context Embeddin." ACCV (2020). [Paper] [Code]

  • DAL: Yanlin Qian, Alan Lukežič, Matej Kristan, Joni-Kristian Kämäräinen, Jiri Mata
    "DAL - A Deep Depth-aware Long-term Tracker" ICPR (2020). [paper] RGB-D Long-term

  • GlobalTrack: Lianghua Huang, Xin Zhao, Kaiqi Huang.
    "GlobalTrack: A Simple and Strong Baseline for Long-term Tracking." AAAI (2020). [Paper] [Code]

  • SPLT: Bin Yan, Haojie Zhao, Dong Wang, Huchuan Lu, Xiaoyun Yang.
    "Skimming-Perusal' Tracking: A Framework for Real-Time and Robust Long-Term Tracking." ICCV (2019). [Paper] [Code]
    An improved (much faster) version of VOT2018-LT Winner🌟

  • flow_MDNet_RPN: Han Wu, Xueyuan Yang, Yong Yang, Guizhong Liu.
    "Flow Guided Short-term Trackers with Cascade Detection for Long-term Tracking." ICCVW (2019). [Paper]

  • OTR: Ugur Kart, Alan Lukezic, Matej Kristan, Joni-Kristian Kamarainen, Jiri Matas.
    "Object Tracking by Reconstruction with View-Specific Discriminative Correlation Filters." CVPR (2019). [Paper] [Code] RGB-D Long-term

  • SiamRPN++: Bo Li, Wei Wu, Qiang Wang, Fangyi Zhang, Junliang Xing, Junjie Yan. "SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks." CVPR (2019). [Paper] [Code]

  • MBMD: Yunhua Zhang, Dong Wang, Lijun Wang, Jinqing Qi, Huchuan Lu.
    "Learning regression and verification networks for long-term visual tracking." Arxiv (2018).
    [Paper] [Code] [Journal Version] VOT2018-LT Winner🌟

  • MMLT: Hankyeol Lee, Seokeon choi, Changick Kim.
    "A Memory Model based on the Siamese Network for Long-term Tracking." ECCVW (2018). [Paper] [Code]

  • FuCoLoT: Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř, Jiří Matas and Matej Kristan.
    "FuCoLoT - A Fully-Correlational Long-Term Tracker." ACCV (2018). [Paper] [Code]

Long-term Trackers modified from Short-term Ones

  • SiamDW: Zhipeng Zhang, Houwen Peng.
    "Deeper and Wider Siamese Networks for Real-Time Visual Tracking." CVPR (2019). [Paper] [Code] VOT2019 RGB-D Winner🌟 Denoted as "SiamDW_D" "SiamDW_LT", see the VOT2019 official report [vot2019code]

  • DaSiam_LT: Zheng Zhu, Qiang Wang, Bo Li, Wei Wu, Junjie Yan, Weiming Hu.
    "Distractor-Aware Siamese Networks for Visual Object Tracking." ECCV (2018). [paper] [code] VOT2018-LT Runner-up🌟

Early Long-term Trackers (before 2018)

  • PTAV: Heng Fan, Haibin Ling.
    "Parallel Tracking and Verifying: A Framework for Real-Time and High Accuracy Visual Tracking." ICCV (2017).
    [paper] [supp] [project] [code]

  • EBT: Gao Zhu, Fatih Porikli, Hongdong Li.
    "Beyond Local Search: Tracking Objects Everywhere with Instance-Specific Proposals." CVPR (2016).
    [paper] [exe]

  • LCT: Chao Ma, Xiaokang Yang, Chongyang Zhang, Ming-Hsuan Yang.
    "Long-term Correlation Tracking." CVPR (2015).
    [paper] [project] [github]

  • MUSTer: Zhibin Hong, Zhe Chen, Chaohui Wang, Xue Mei, Danil Prokhorov, Dacheng Tao.
    "MUlti-Store Tracker (MUSTer): a Cognitive Psychology Inspired Approach to Object Tracking." CVPR (2015).
    [paper] [project]

  • CMT: Georg Nebehay, Roman Pflugfelder.
    "Clustering of Static-Adaptive Correspondences for Deformable Object Tracking." CVPR (2015).
    [paper] [project] [github]

  • SPL: James Steven Supančič III, Deva Ramanan.
    "Self-paced Learning for Long-term Tracking." CVPR (2013).
    [paper] [github]

  • TLD: Zdenek Kalal, Krystian Mikolajczyk, Jiri Matas.
    "Tracking-Learning-Detection." TPAMI (2012).
    [paper] [project]

Measurement & Discussion:

  • Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř, Jiří Matas, Matej Krista. "Performance Evaluation Methodology for Long-Term Visual Object Tracking." ArXiv (2019). [paper]

  • Alan Lukežič, Luka Čehovin Zajc, Tomáš Vojíř, Jiří Matas, Matej Kristan. "Now You See Me: Evaluating Performance in Long-term Visual Tracking." ArXiv (2018). [paper]

  • Shyamgopal Karthik, Abhinav Moudgil, Vineet Gandhi. "Exploring 3 R's of Long-term Tracking: Re-detection, Recovery and Reliability." WACV (2020). [paper]

Previous Benchmark Results:

  • VOT2019-LT/VOT2020-LT/VOT2021-LT

    Tracker F-Score Speed (fps) Paper/Code
    KeepTrack (ICCV21) 0.709 18 (RTX 2080Ti) Paper/Code
    STARK (ICCV21) 0.701 32 (Tesla V100) Paper/Code
    LTMU (CVPR20) 0.697 13 (RTX 2080Ti) Paper/Code
    LT_DSE 0.695 N/A N/A
    LTMU_B 0.691 N/A Paper/Code
    DMTrack (CVPR21) 0.687 31 (Titan XP) Paper/Project
    Megtrack 0.687 N/A N/A
    CLGS 0.674 N/A N/A
    SiamDW_LT 0.665 N/A N/A
    SPLT (ICCV19) 0.587 26 (GTX 1080Ti) Paper/Code
    mbdet 0.567 N/A N/A
    SiamRPNsLT 0.556 N/A N/A
    Siamfcos-LT 0.520 N/A N/A
    CooSiam 0.508 N/A N/A
    ASINT 0.505 N/A N/A
    FuCoLoT 0.411 N/A N/A
    • Most results are obtained from the original VOT2019 and VOT2020 reports.
    • All sequences and settings are same in the VOT2019-LT, VOT2020-LT and VOT2021-LT challenges.
    • We will not update the results [marked by 2022-11]. Please focus on VOT2022-LT.

  • VOT2018-LT:

    Tracker F-Score Speed (fps) Paper/Code
    LTMU (CVPR20) 0.690 13 (RTX 2080Ti) Paper/Code
    Siam R-CNN (CVPR20) 0.668 5 (Tesla V100) Paper/Code
    PG-Net (ECCV20) 0.642 N/A Paper/Code
    SiamRPN++ 0.629 35 (Titan XP) Paper/Code
    SPLT (ICCV19) 0.622 26 (GTX 1080Ti) Paper/Code
    MBMD (Arxiv) 0.610 4 (GTX 1080Ti) Paper/Code
    DaSiam_LT (ECCV18) 0.607 110 (TITAN X) Paper/Code
    • MBMD and DaSiam_LT is the winner and runner-up in the original VOT2018_LT report.
    • VOT2018-LT is a subset of VOT2019-LT; thus, we will not update the results [marked by 2021-08].

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