2022CVPR目标跟踪最新论文

多目标跟踪领域最新论文概况

多目标跟踪

  • 多目标跟踪领域最新论文概况
  • 一、2022年多目标跟踪论文
    • CVPR2022:
      • 1、Global Tracking Transformers
      • 2、Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking
      • 3、Unified Transformer Tracker for Object Tracking
      • 4、TR-MOT: Multi-Object Tracking by Reference
      • 5、MeMOT: Multi-Object Tracking with Memory
      • 6、Learning of Global Objective for Network Flow in Multi-Object Tracking
    • 其他
  • 二、2021年多目标跟踪论文
    • CVPR2021
      • 1、Track to Detect and Segment: An Online Multi-Object Tracker
      • 2、 Learning a Proposal Classifier for Multiple Object Tracking(用于多对象跟踪的分类器)
      • 3、Online Multiple Object Tracking with Cross-Task Synergy(具有跨任务协同作用的在线多对象跟踪)
      • 4、Multiple Object Tracking with Correlation Learning(相关学习的多目标跟踪)
      • 5、TransTrack: Multiple-Object Tracking with Transformer
      • 6、TransCenter: Transformers with Dense Queries for Multiple-Object Tracking
      • 7、TrackFormer: Multi-Object Tracking with Transformers
      • 8、ByteTrack: Multi-Object Tracking by Associating Every Detection Box

一、2022年多目标跟踪论文

CVPR2022:

1、Global Tracking Transformers

论文地址:https://arxiv.org/abs/2203.13250
GTR代码: https://github.com/xingyizhou/GTR

论文解读及笔记:https://blog.csdn.net/qq_39821101/article/details/123954724?spm=1001.2014.3001.5501

2、Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking

论文:https://arxiv.org/pdf/2203.14360.pdf
OC_SORT代码:https://github.com/noahcao/OC_SORT

论文解读及笔记:
https://blog.csdn.net/qq_39821101/article/details/124091875

3、Unified Transformer Tracker for Object Tracking

论文地址:https://arxiv.org/abs/2203.15175
Trackron源码:https://github.com/Flowerfan/Trackron

论文解读及笔记:

4、TR-MOT: Multi-Object Tracking by Reference

论文地址:https://arxiv.org/abs/2203.16621

5、MeMOT: Multi-Object Tracking with Memory

论文地址:https://arxiv.org/pdf/2203.16761.pdf

6、Learning of Global Objective for Network Flow in Multi-Object Tracking

论文地址:https://arxiv.org/abs/2203.16210

其他

二、2021年多目标跟踪论文

CVPR2021

1、Track to Detect and Segment: An Online Multi-Object Tracker

论文地址:https://openaccess.thecvf.com/content/CVPR2021/papers/Wu_Track_To_Detect_and_Segment_An_Online_Multi-Object_Tracker_CVPR_2021_paper.pdf
TraDeS代码:https://github.com/JialianW/TraDeS

2、 Learning a Proposal Classifier for Multiple Object Tracking(用于多对象跟踪的分类器)

论文地址:https://arxiv.org/abs/2103.07889
LPC_MOT代码:https://github.com/daip13/LPC_MOT

3、Online Multiple Object Tracking with Cross-Task Synergy(具有跨任务协同作用的在线多对象跟踪)

论文地址:https://arxiv.org/abs/2104.00380
TADAM代码:https://github.com/songguocode/TADAM

4、Multiple Object Tracking with Correlation Learning(相关学习的多目标跟踪)

论文地址:https://arxiv.org/abs/2104.03541
corrTracker代码:未公开

5、TransTrack: Multiple-Object Tracking with Transformer

论文地址:http://arxiv.org/abs/2012.15460
TransTrack源码:https://github.com/PeizeSun/TransTrack

论文解读及笔记:
参考论文解读:https://blog.csdn.net/zhouchen1998/article/details/112427217

6、TransCenter: Transformers with Dense Queries for Multiple-Object Tracking

论文地址:https://arxiv.org/abs/2103.15145
TransCenter源码:https://github.com/yihongxu/transcenter

论文解读及笔记:

7、TrackFormer: Multi-Object Tracking with Transformers

论文地址:https://arxiv.org/abs/2101.02702
TrackFormer源码:https://github.com/timmeinhardt/trackformer

论文解读及笔记:

8、ByteTrack: Multi-Object Tracking by Associating Every Detection Box

论文地址:https://arxiv.org/pdf/2110.06864.pdf
代码地址:https://github.com/ifzhang/ByteTrack
论文解读及笔记:
1、https://blog.csdn.net/qq_39821101/article/details/121031225?spm=1001.2014.3001.5501
2、https://blog.csdn.net/qq_39821101/article/details/124140688

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