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MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking
Transformer-based object trackers are renowned for their strong performance, yet dense token processing often leads to prohibitive computational cost, limiting real-time deployment on edge devices. While recent works explore token pruning to reduce computation, they often stop short of an end-to-end sparse pipeline, as early-layer token scores can be noisy without a motion prior, and many trackers ultimately fall back to dense reshaping to feed the dense prediction head that partially negates the savings. We introduce Motion-aware Sparse Tracker (MaST), a sparse tracking framework that makes s
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-08-25T10:25:15.000Z
First collected: 2026-09-21T10:02:02.728Z. This is not the publication date.