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Multi-Stream Deep Similarity Learning Networks for Visual Tracking
2017
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence
Visual tracking has achieved remarkable success in recent decades, but it remains a challenging problem due to appearance variations over time and complex cluttered background. In this paper, we adopt a tracking-by-verification scheme to overcome these challenges by determining the patch in the subsequent frame that is most similar to the target template and distinctive to the background context. A multi-stream deep similarity learning network is proposed to learn the similarity comparison
doi:10.24963/ijcai.2017/301
dblp:conf/ijcai/LiKF17
fatcat:pqxfbkhtwbg2nlrunfpyemckc4