VideoCube Evaluation Server

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

Submmition Count:

1 submissions.

Performance:

Method N-PRE PRE Hardware Language Date(UTC) Results Reports
1 KCF 0.141 0.005 Titan RTX python 2021-12-04, 14:31:36 results.zip reports.json