无感觉 发表于 2025-3-21 16:53:05

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禁止,切断 发表于 2025-3-21 20:55:48

Visual Tracking in Continuous Appearance Space via Sparse Coding dynamic change of object appearance by adaptively updating the object template model using the learned dictionary, and at the same time can avoid drifting by using representation error for supervision. Our method thus can perform more robust than previous methods in dynamic scenes of gradual change

表示向下 发表于 2025-3-22 02:40:34

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STRIA 发表于 2025-3-22 07:56:12

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细查 发表于 2025-3-22 09:06:57

Robust Registration-Based Tracking by Sparse Representation with Model Update algorithm which iteratively solves the LASSO and classical Lucas-Kanade by optimizing one while keeping another fixed. Unlike existing sparsity-based work that uses exemplar templates as the object model, we explore the low-dimensional linear subspace of the object appearances for object representa

ALIBI 发表于 2025-3-22 14:37:03

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ALIBI 发表于 2025-3-22 18:04:27

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Confess 发表于 2025-3-22 23:25:20

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难听的声音 发表于 2025-3-23 02:35:20

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Gyrate 发表于 2025-3-23 08:11:56

Royal Navy Metric Warning Radar, 1935–45tracklet belonging to the same object. Furthermore, we give a near-optimal algorithm based on globally greedy strategy to deal with spatio-temporal clustering, which runs linearly with the number of tracklets. We quantitatively evaluate the performance of our method on three challenging data sets an
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查看完整版本: Titlebook: Computer Vision -- ACCV 2012; 11th Asian Conferenc Kyoung Mu Lee,Yasuyuki Matsushita,Zhanyi Hu Conference proceedings 2013 Springer-Verlag