AnyTrack: Unifying Visual Object Tracking with Any Modalities 文章

ArXiv CS.CV2026-08-10PAPERen作者: Hao Li, Yunzhi Zhuge, Wenning Hao, Pingping Zhang, Xiaoxiong Zhang, Dong Wang, Huchuan Lu

详细信息

来源站点
ArXiv CS.CV
作者
Hao Li, Yunzhi Zhuge, Wenning Hao, Pingping Zhang, Xiaoxiong Zhang, Dong Wang, Huchuan Lu
文章类型
PAPER
语言
en
发布日期
2026-08-10

摘要

arXiv:2608.06773v1 Announce Type: new Abstract: Visual object tracking aims to continuously locate specific targets within sequential frames, evolving from single-modal methods to multi-modal ones. However, existing multi-modal trackers are typically designed for fixed modality combinations, requiring separate models for different inputs. This leads to a poor adaptability to missing or imperfect modalities, and limited generalization. To address these issues, we propose a novel unified framework called AnyTrack for object tracking with any modalities. Specifically, we design a Modality-aware Interaction Module (MIM) to facilitate dynamic interaction across diverse modalities. This module bridges modality discrepancies and aggregates temporal cues to maintain spatio-temporal consistency during cross-modal interaction. Furthermore, we introduce a Context Understanding Module (CUM) to establish spatial correspondence between visual features and target locations via global-local prompts.

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