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MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

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

First collected: 2026-09-21T10:02:02.728Z. This is not the publication date.