CSTrack: Rethinking the competition between detection and ReID in Multi-Object Tracking


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Benchmark:

Short name:

CSTrack

Detector:

Private

Description:

CSTrack proposes a strong ReID based one-shot MOT framework. It includes a novel cross-correlation network that can effectively impel the separate branches to learn task-dependent representations, and a scale-aware attention network that learns discriminative embeddings to improve the ReID capability. This work also provides an analysis of the weak data association ability in one-shot MOT methods. Our improvements make the data association ability of our one-shot model is comparable to two-stage methods while running more faster.

Reference:

C. Liang, Z. Zhang, Y. Lu, X. Zhou, B. Li. Rethinking the competition between detection and ReID in Multi-Object Tracking. In arXiv:2010.12138 [cs], 2020.

Last submitted:

November 18, 2020 (3 years ago)

Published:

October 21, 2020 at 13:07:50 CET

Submissions:

2

Project page / code:

Open source:

Yes

Hardware:

RTX2080ti

Runtime:

15.8 Hz

Benchmark performance:

Sequence MOTA IDF1 HOTA MT ML FP FN Rcll Prcn AssA DetA AssRe AssPr DetRe DetPr LocA FAF ID Sw. Frag
MOT1675.673.359.8325 (42.8)125 (16.5)9,64633,77781.593.958.261.863.576.667.477.783.21.61,121 (13.8)2,450 (30.1)

Detailed performance:

Sequence MOTA IDF1 HOTA MT ML FP FN Rcll Prcn AssA DetA AssRe AssPr DetRe DetPr LocA FAF ID Sw. Frag
MOT16-0157.062.950.8871122,60459.397.154.147.758.481.049.881.684.20.235101
MOT16-0389.282.067.613404,5116,56193.795.663.872.068.979.378.079.583.63.0263632
MOT16-0661.064.251.277575143,82566.893.851.551.259.472.555.177.383.10.4164286
MOT16-0765.662.149.12331,0114,46372.792.144.554.349.870.159.775.882.92.0144337
MOT16-0852.848.442.52522,3245,28868.483.138.648.145.960.656.368.582.13.7295456
MOT16-1258.768.154.926186352,74266.989.758.651.664.178.557.176.584.90.749177
MOT16-1451.361.242.932385398,29455.195.046.240.349.874.142.773.679.50.7171461

Raw data: