MPTrack: Visual Tracking with Reliable Motion Prompts

Recently, the attention mechanism has been introduced into object tracking, making significant improvements in tracking performance. However, the tracking target often undergoes deformation during tracking, which can easily lead to the loss of the target. In this paper, we design the motion perception unit (MPU) to enhance tracking stability. The MPU generates motion prompts rich in dynamic target appearance information and integrates them into object modeling. This integration allows our tracker to better adapt to changes in target motion and appearance, improving the adaptability to the target motion. Extensive experiments demonstrate that our tracker MPTrack outperforms all state-of-the-art trackers on five widely recognized benchmarks, including GOT-10k, TrackingNet, LaSOText, UAV123, and TNL2K, while running at real-time speed.

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Published
2024-08-30
DOI
https://doi.org/10.1145/3708282.3708292
Primary Topic
Video Surveillance and Tracking Methods
Type
article
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article

MPTrack: Visual Tracking with Reliable Motion Prompts

Lunbo Li, Songtao Sun
Video Surveillance and Tracking Methods
article

MPTrack: Visual Tracking with Reliable Motion Prompts

Lunbo Li, Songtao Sun
article en

Abstract

Recently, the attention mechanism has been introduced into object tracking, making significant improvements in tracking performance. However, the tracking target often undergoes deformation during tracking, which can easily lead to the loss of the target. In this paper, we design the motion perception unit (MPU) to enhance tracking stability. The MPU generates motion prompts rich in dynamic target appearance information and integrates them into object modeling. This integration allows our tracker to better adapt to changes in target motion and appearance, improving the adaptability to the target motion. Extensive experiments demonstrate that our tracker MPTrack outperforms all state-of-the-art trackers on five widely recognized benchmarks, including GOT-10k, TrackingNet, LaSOText, UAV123, and TNL2K, while running at real-time speed.

Nanjing University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 75%
Video Surveillance and Tracking Methods
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MPTrack: Visual Tracking with Reliable Motion Prompts — Lunbo Li, Songtao Sun · (2024) | TGRS Research Map | TGRS