Benchmark:

MOT16 | MOT17 | MOT20 | MOT15 |

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:

https://github.com/JudasDie/SOTS

Open source:

Yes

Hardware:

RTX2080ti

Runtime:

15.8 Hz

Benchmark performance:

Detailed performance:

Raw data:

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