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arXiv 提交日期: 2026-02-23
📄 Abstract - Accurate Planar Tracking With Robust Re-Detection

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. The code and the re-annotations are available at this https URL

顶级标签: computer vision systems
详细标签: planar tracking homography estimation segmentation tracking re-detection benchmark 或 搜索:

基于鲁棒重检测的精确平面跟踪 / Accurate Planar Tracking With Robust Re-Detection


1️⃣ 一句话总结

这篇论文提出了两种新的平面跟踪方法,通过结合先进的图像分割技术和鲁棒的重检测机制,在目标外观变化时也能实现高精度的跟踪,并在主流测试集上取得了目前最好的性能。

源自 arXiv: 2602.19624