Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking

@article{Zhu2021LearningDC,
  title={Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking},
  author={Pengfei Zhu and Hongtao Yu and Kaihua Zhang and Yu Wang and Shuai Zhao and Lei Wang and Tianzhu Zhang and Qinghua Hu},
  journal={IEEE transactions on neural networks and learning systems},
  year={2021},
  volume={PP}
}
  • Pengfei ZhuHongtao Yu Q. Hu
  • Published 23 November 2021
  • Computer Science
  • IEEE transactions on neural networks and learning systems
Recently, template-based trackers have become the leading tracking algorithms with promising performance in terms of efficiency and accuracy. However, the correlation operation between query feature and the given template only achieves accurate target localization, but is prone to state estimation error, especially when the target suffers from severe deformation. To address this issue, segmentation-based trackers are proposed that use per-pixel matching to improve the tracking performance of… 

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