Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking
Abstract
Discriminative Correlation Filters (DCF) have demonstrated excellent performance for visual object tracking. The key to their success is the ability to efficiently exploit available negative data b ...
Cite
Text
Danelljan et al. "Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking." European Conference on Computer Vision, 2016. doi:10.1007/978-3-319-46454-1_29Markdown
[Danelljan et al. "Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking." European Conference on Computer Vision, 2016.](https://mlanthology.org/eccv/2016/danelljan2016eccv-beyond/) doi:10.1007/978-3-319-46454-1_29BibTeX
@inproceedings{danelljan2016eccv-beyond,
title = {{Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking}},
author = {Danelljan, Martin and Robinson, Andreas and Khan, Fahad Shahbaz and Felsberg, Michael},
booktitle = {European Conference on Computer Vision},
year = {2016},
pages = {472-488},
doi = {10.1007/978-3-319-46454-1_29},
url = {https://mlanthology.org/eccv/2016/danelljan2016eccv-beyond/}
}