Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking

CVPR 2018 Feng LiCheng TianWangmeng ZuoLei ZhangMing-Hsuan Yang

Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been suggested to resolve this issue by enforcing spatial penalty on DCF coefficients, which, inevitably, improves the tracking performance at the price of increasing complexity... (read more)

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Evaluation results from the paper


Task Dataset Model Metric name Metric value Global rank Compare
Visual Object Tracking VOT2017/18 STRCF Expected Average Overlap (EAO) 0.345 # 4