Learning Low-Rank and Sparse Discriminative Correlation Filters for Coarse-to-Fine Visual Object Tracking-Reference-Cited by-同舟云学术

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Learning Low-Rank and Sparse Discriminative Correlation Filters for Coarse-to-Fine Visual Object Tracking

Published:2020-10 Issue:10 Volume:30 Page:3727-3739
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Xu Tianyang^ORCID,Feng Zhen-Hua^ORCID,Wu Xiao-Jun,Kittler Josef

Funder

National Natural Science Foundation of China

111 Project of Ministry of Education of China

EPSRC Programme

EPSRC/dstl/MURI Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Media Technology

Link

http://xplorestaging.ieee.org/ielx7/76/9210915/08854808.pdf?arnumber=8854808

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2. Memory Prompt for Spatiotemporal Transformer Visual Object Tracking;IEEE Transactions on Artificial Intelligence;2024-08

3. Learning Feature Restoration Transformer for Robust Dehazing Visual Object Tracking;International Journal of Computer Vision;2024-07-12

4. Joint Response and Background Learning for UAV Visual Tracking;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13

5. Multibeam Forward-Looking Sonar Video Object Tracking Using Truncated - Sparsity and Aberrances Repression Regularization;IEEE Robotics and Automation Letters;2024-02

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