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:

ECO

Long Name:

ECO

Method Description:

n/a

Project Page:

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

Paper URL:

https://ieeexplore.ieee.org/document/8100216

Code URL:

https://github.com/visionml/pytracking

Hardware:

Titan RTX

Language:

python

Author:

Official

LaTex Bibtex:

@INPROCEEDINGS{8100216, author={Danelljan, Martin and Bhat, Goutam and Khan, Fahad Shahbaz and Felsberg, Michael}, booktitle={2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)}, title={ECO: Efficient Convolution Operators for Tracking}, year={2017}, volume={}, number={}, pages={6931-6939}, doi={10.1109/CVPR.2017.733}}

Submissions (R-OPE Mechanism)

Submmition Count:

1 submissions.

Performance:

Method N-PRE PRE SRIoU SRDIoU SRGIoU Robust Hardware Language Date(UTC) Results Reports
1 ECO 0.745 0.329 0.490 0.479 0.476 0.733 Titan RTX python 2022-03-02, 10:18:28 results.zip reports.json