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:

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 (OPE Mechanism)

Submmition Count:

1 submissions.

Performance:

Method N-PRE PRE SRIoU SRDIoU SRGIoU Hz Hardware Language Date(UTC)↓ Results Reports
1 ECO 0.244 0.033 0.120 0.106 0.107 8.80 fps Titan RTX python 2021-11-14, 06:10:27 results.zip reports.json