The article introduces AQATrack, a novel adaptive tracker with spatio-temporal transformers. It focuses on capturing instantaneous appearance changes using autoregressive queries and a novel attention mechanism. The proposed method aims to combine static appearance and instantaneous changes for robust tracking. Extensive experiments show significant improvements in performance across various tracking benchmarks. The article also discusses related work in visual object tracking based on spatial features and the importance of spatio-temporal information in improving discriminative ability. The method is compared with other state-of-the-art trackers, showcasing its competitive performance.
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by Jinxia Xie,B... às arxiv.org 03-19-2024
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