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Found 5 papers, 3 papers with code
DMSSN: Distilled Mixed Spectral-Spatial Network for Hyperspectral Salient Object Detection
To address these challenges, we propose a novel approach termed the Distilled Mixed Spectral-Spatial Network (DMSSN), comprising a Distilled Spectral Encoding process and a Mixed Spectral-Spatial Transformer (MSST) feature extraction network.
Multi-step Temporal Modeling for UAV Tracking
This module leverages temporal information to refresh the template feature, yielding a more precise correlation map.
Factorization Vision Transformer: Modeling Long Range Dependency with Local Window Cost
Accordingly, we propose a novel factorization self-attention mechanism (FaSA) that enjoys both the advantages of local window cost and long-range dependency modeling capability.
BACTrack: Building Appearance Collection for Aerial Tracking
At the same time, the appearance discriminator employs an online adaptive template-update strategy to ensure that the collected multiple templates remain reliable and diverse, allowing them to closely follow rapid changes in the target's appearance and suppress background interference during tracking.
Spectrum-driven Mixed-frequency Network for Hyperspectral Salient Object Detection
The Spectral Saliency approximates the region of salient objects, while the Spectral Edge captures edge information of salient objects.
