VideoCube Evaluation Server (R-OPE Mechanism with Full Version)

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)↓ Reports
1 LTMU 0.799 0.429 0.585 0.576 0.577 0.741 Titan RTX python 2022-03-02, 10:21:54 reports.json