Visual Tracking via Adaptive Spatially-Regularized Correlation Filters

CVPR 2019 Kenan Dai Dong Wang Huchuan Lu Chong Sun Jianhua Li

In this work, we propose a novel adaptive spatially-regularized correlation filters (ASRCF) model to simultaneously optimize the filter coefficients and the spatial regularization weight. First, this adaptive spatial regularization scheme could learn an effective spatial weight for a specific object and its appearance variations, and therefore result in more reliable filter coefficients during the tracking process... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Visual Tracking OTB-100 ASRCF AUC 0.692 # 1