Feature-Level Fusion Network for Hyperspectral Object Tracking via Mixed Multi-Head Self-Attention Learning

Feature-Level Fusion Network for Hyperspectral Object Tracking via Mixed Multi-Head Self-Attention Learning

Hyperspectral object tracking has emerged as a promising task in visual object tracking. The rich spectral information within hyperspectral images benefits the accurate tracking in challenging scenarios. The performances of existing hyperspectral object tracking networks are constrained by neglectin...

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Bibliographic Details
Main Authors: Long Gao, Langkun Chen, Yan Jiang, Bobo Xi, Weiying Xie, Yunsong Li
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Remote Sensing
Subjects:
feature fusion
mixed multi-head attention
Transformer
hyperspectral object tracking
Online Access:https://www.mdpi.com/2072-4292/17/6/997
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