VideoCube Evaluation Server (R-OPE Mechanism)

Submit your tracking results on VideoCube to this website and evaluate the performance. Leaderboard will be updated immediately once the results are evaluated.

Tracker

Short Name:

LTMU

Long Name:

LTMU

Method Description:

n/a

Project Page:

https://github.com/Daikenan/LTMU

Paper URL:

https://ieeexplore.ieee.org/document/9156764

Code URL:

https://github.com/Daikenan/LTMU

Hardware:

Titan RTX

Language:

python

Author:

Official

LaTex Bibtex:

@INPROCEEDINGS{9156764, author={Dai, Kenan and Zhang, Yunhua and Wang, Dong and Li, Jianhua and Lu, Huchuan and Yang, Xiaoyun}, booktitle={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, title={High-Performance Long-Term Tracking With Meta-Updater}, year={2020}, volume={}, number={}, pages={6297-6306}, doi={10.1109/CVPR42600.2020.00633}}

Submissions (R-OPE Mechanism)

Submmition Count:

1 submissions.

Performance:

Method N-PRE PRE SRIoU SRDIoU SRGIoU Robust Hardware Language Date(UTC) Results Reports
1 LTMU 0.799 0.429 0.585 0.576 0.577 0.741 Titan RTX python 2022-03-02, 10:21:54 results.zip reports.json