Lightweight Spatial-Temporal Contextual Aggregation Siamese Network for Unmanned Aerial Vehicle Tracking

Lightweight Spatial-Temporal Contextual Aggregation Siamese Network for Unmanned Aerial Vehicle Tracking

Benefiting from the powerful feature extraction capability of deep learning, the Siamese tracker stands out due to its advanced tracking performance. However, constrained by the complex backgrounds of aerial tracking, such as low resolution, occlusion, similar objects, small objects, scale variation...

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Bibliographic Details
Main Authors: Qiqi Chen, Jinghong Liu, Faxue Liu, Fang Xu, Chenglong Liu
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Drones
Subjects:
aerial tracking
atrous convolution
Siamese tracker
temporal context
Online Access:https://www.mdpi.com/2504-446X/8/1/24

Internet

https://www.mdpi.com/2504-446X/8/1/24

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