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arXiv Computer Vision By Shiao Wang, Xiao Wang, Yuhe Ding, Jiarui Xu, Zikang Yan, Bo Jiang, Yonghong Tian, Jin Tang

UniMergeTrack: Hierarchical Model Merging for General RGB-X Visual Object Tracking

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UniMergeTrack introduces a hierarchical model merging strategy for RGB-X visual object tracking, combining independently trained modality-specific trackers into a unified framework. The method merges transferable backbones using high‑pass‑filtered merging, aligns tracking heads with optimal transport‑guided channel alignment, and fine‑tunes with distribution alignment to integrate cross‑task knowledge while preserving modality cues. Experiments on multiple benchmarks show state‑of‑the‑art or competitive performance across RGB‑Thermal, RGB‑Event, and RGB‑Depth tracking tasks, with strong generalization to unseen datasets.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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