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:

KCF

Long Name:

KCF

Method Description:

n/a

Project Page:

n/a

Paper URL:

https://arxiv.org/abs/1404.7584

Code URL:

https://github.com/foolwood/KCF

Hardware:

Titan RTX

Language:

python

Author:

Official

LaTex Bibtex:

@ARTICLE{6870486, author={Henriques, João F. and Caseiro, Rui and Martins, Pedro and Batista, Jorge}, journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, title={High-Speed Tracking with Kernelized Correlation Filters}, year={2015}, volume={37}, number={3}, pages={583-596}, doi={10.1109/TPAMI.2014.2345390}}

Submissions (R-OPE Mechanism)

Submmition Count:

1 submissions.

Performance:

Method N-PRE PRE SRIoU SRDIoU SRGIoU Robust Hardware Language Date(UTC)↓ Results Reports
1 KCF 0.640 0.252 0.411 0.396 0.394 0.724 Titan RTX python 2022-03-02, 10:21:11 results.zip reports.json