Accurate Planar Tracking With Robust Re-Detection

Jonáš Šerých, Jiří Matas

2026


A comparison of the previous state-of-the-art WOFT with the proposed WOFTSAM.

Abstract

We present SAM-H and WOFTSAM, novel planar trackers that combine robust long-term segmentation tracking provided by SAM 2 with 8 degrees-of-freedom homography pose estimation. SAM-H estimates homographies from segmentation mask contours and is thus highly robust to target appearance changes. WOFTSAM significantly improves the current state-of-the-art planar tracker WOFT by exploiting lost target re-detection provided by SAM-H. The proposed methods are evaluated on POT-210 and PlanarTrack tracking benchmarks, setting the new state-of-the-art performance on both. On the latter, they outperform the second best by a large margin, +12.4 and +15.2pp on the p@15 metric. We also present improved ground-truth annotations of initial PlanarTrack poses, enabling more accurate benchmarking in the high-precision p@5 metric.

PlanarTrack Initial Frame Re-Annotation

We have carefully manually re-annotated the initial frames of the PlanarTrack TST dataset as described in the paper. We provide the re-annotation here.

Bibtex

Please cite our paper in case you use its source code, results, or the re-annotation. 
@article{serych2026woftsam,
  title={Accurate Planar Tracking With Robust Re-Detection},
  author={Serych, Jonas and Matas, Jiri},
  journal={arXiv preprint arXiv:2602.19624},
  year={2026}
}

Acknowledgments

This work was supported by the National Recovery Plan project CEDMO 2.0 NPO (MPO 60273/24/21300/21000), the EC Digital Europe Programme project CEDMO 2.0 no. 101158609, and by the Research Center for Informatics project CZ.02.1.01/0.0/0.0/16_019/0000765 funded by OP VVV.