VideoCube Evaluation Server (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:

SuperDiMP

Long Name:

SuperDiMP

Method Description:

n/a

Project Page:

https://martin-danelljan.github.io/

Paper URL:

https://ieeexplore.ieee.org/document/9157124

Code URL:

https://github.com/visionml/pytracking

Hardware:

Titan RTX

Language:

Python

Author:

Official

LaTex Bibtex:

@INPROCEEDINGS{9157124, author={Danelljan, Martin and Van Gool, Luc and Timofte, Radu}, booktitle={2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)}, title={Probabilistic Regression for Visual Tracking}, year={2020}, volume={}, number={}, pages={7181-7190}, doi={10.1109/CVPR42600.2020.00721}}

Submissions (OPE Mechanism)

Submmition Count:

1 submissions.

Performance:

Method N-PRE PRE SRIoU SRDIoU SRGIoU Hz Hardware Language Date(UTC)↓ Reports
1 SuperDiMP 0.600 0.284 0.440 0.428 0.432 6.61 fps Titan RTX Python 2021-11-14, 07:04:55 reports.json