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Distractor-aware deep regression for visual tracking

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Academic year: 2019

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Figure

Figure 1. Overview of the proposed deep regression network. The left-side blocks are the fixed-featureThe blue blocks represent the 1extractor backbone
Figure 2. ((a) Sliding sampled region of interest (ROI) centered on the target. (b) Obvious semanticdistractors labeled in red bounding boxes
Figure 3. Three types of feature connection. (1) Independent connection that is used in traditionalVGG16correlation-filter trackers (e.g., ECO [32])
Figure 5. Precision and success plots using one-pass evaluation on the OTB-13 and OTB-15 datasets.The performance score for each tracker is shown in the legend.Our tracker achieves leadingperformance among the evaluated trackers
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