/Long-term-Visual-Tracking

Long-term Visual Tracking:

Recent Long-term Trackers

  • 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🌟 This work is an improved version of the VOT2019-LT winner, [LT_DSE].

  • Siam R-CNN: Paul Voigtlaender, Jonathon Luiten, Philip H.S. Torr, Bastian Leibe.
    "Siam R-CNN: Visual Tracking by Re-Detection." ArXiv (2019). [paper]

  • DAL: Yanlin Qian, Alan Lukežič, Matej Kristan, Joni-Kristian Kämäräinen, Jiri Mata
    "DAL - A Deep Depth-aware Long-term Tracker" ArXiv (2019). [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]

  • 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] 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

  • 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]

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

Benchmark

  • 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] [project] 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.

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]

Resources: