2022CVPR目标跟踪最新论文

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

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