Staple: Complementary Learners for Real-Time Tracking

CVPR 2016 Luca BertinettoJack ValmadreStuart GolodetzOndrej MiksikPhilip Torr

Correlation Filter-based trackers have recently achieved excellent performance, showing great robustness to challenging situations exhibiting motion blur and illumination changes. However, since the model that they learn depends strongly on the spatial layout of the tracked object, they are notoriously sensitive to deformation... (read more)

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Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK LEADERBOARD
Visual Object Tracking TrackingNet STAPLE_CA Precision 46.72 # 6
Normalized Precision 60.84 # 6
Accuracy 53.59 # 6

Methods used in the Paper


METHOD TYPE
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