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
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- CVPR2022:
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- 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
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- 二、2021年多目标跟踪论文
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- CVPR2021
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- 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