Title | Prompting for Multi-Modal Tracking |
Author | |
Corresponding Author | Feng Zheng |
DOI | |
Publication Years | 2022-08-01
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Conference Name | The 30th ACM International Conference on Multimedia
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Conference Date | 2022/10/10-2022/10/14
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Conference Place | 里斯本
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Abstract | Multi-modal tracking gains attention due to its ability to be more accurate and robust in complex scenarios compared to traditional RGB-based tracking. Its key lies in how to fuse multi-modal data and reduce the gap between modalities. However, multi-modal tracking still severely suffers from data deficiency, thus resulting in the insufficient learning of fusion modules. Instead of building such a fusion module, in this paper, we provide a new perspective on multimodal tracking by attaching importance to the multi-modal visual prompts. We design a novel multi-modal prompt tracker (ProTrack), which can transfer the multi-modal inputs to a single modality by the prompt paradigm. By best employing the tracking ability of pretrained RGB trackers learning at scale, our ProTrack can achieve high-performance multi-modal tracking by only altering the inputs, even without any extra training on multi-modal data. Extensive experiments on 5 benchmark datasets demonstrate the effectiveness of the proposed ProTrack. |
SUSTech Authorship | First
; Corresponding
|
Language | English
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Data Source | 人工提交
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Publication Status | 在线出版
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Citation statistics |
Cited Times [WOS]:0
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Document Type | Conference paper |
Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/415620 |
Department | Southern University of Science and Technology 工学院_计算机科学与工程系 |
Affiliation | 1.Southern University of Science and Technology, China 2.University of Birmingham, UK 3.University of Electronic Science and Technology of China |
First Author Affilication | Southern University of Science and Technology |
Corresponding Author Affilication | Southern University of Science and Technology |
First Author's First Affilication | Southern University of Science and Technology |
Recommended Citation GB/T 7714 |
Jinyu Yang,Zhe Li,Feng Zheng,et al. Prompting for Multi-Modal Tracking[C],2022.
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