Learning Target-Aware Vision Transformers for Real-Time UAV Tracking-Reference-Cited by-同舟云学术

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Learning Target-Aware Vision Transformers for Real-Time UAV Tracking

Published:2024 Issue: Volume:62 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Li Shuiwang¹^ORCID,Yang Xiangyang¹^ORCID,Wang Xucheng¹^ORCID,Zeng Dan²,Ye Hengzhou¹^ORCID,Zhao Qijun³^ORCID

Affiliation:

1. Guangxi Key Laboratory of Embedded Technology and Intelligent System, Guilin University of Technology, Guilin, China

2. Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

3. College of Computer Science, Sichuan University, Chengdu, China

Funder

Guangxi Natural Science Foundation

Specific Research Project of Guangxi for Research Bases and Talents

Guangxi Key Technologies Research and Development Program

National Natural Science Foundation of China

Sichuan Province Key Research and Development Project

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10568178.pdf?arnumber=10568178

Reference89 articles.

1. SparseTT: Visual Tracking with Sparse Transformers

2. TCTrack: Temporal Contexts for Aerial Tracking

3. Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework

4. Learning residue-aware correlation filters and refining scale for real-time UAV tracking

5. Active Learning for Deep Visual Tracking

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1. Efficient Template Distinction Modeling Tracker With Temporal Contexts for Aerial Tracking;IEEE Transactions on Geoscience and Remote Sensing;2024

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