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Accurate Positioning Siamese Network for Real-Time Object Tracking
2019
IEEE Access
Though end-to-end siamese networks have achieved great performance on object tracking owing to offline pre-training with large datasets. They are still liable to fail to track fast moving object and their accuracy suffers from the cosine window for mitigating background interference. The cosine window will aggravate the boundary effect and have a negative impact on track. In this paper, we propose an accurate positioning siamese network (FPSiam) for real-time object tracking. This approach can
doi:10.1109/access.2019.2924147
fatcat:gfi4iaklqvhspmcn3jnf4sinma