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CLDTracker: A Comprehensive Language Description for visual Tracking
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AI
DOI：10.1016/j.inffus.2025.103374.png)
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Abstract
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• Introduce comprehensive bag of textual descriptions for VOT tracking. • Provide a comprehensive bag of textual descriptions for six VOT datasets. • Propose TTFUM to update target text features over time. • Fuse visual and textual features using attention-based correlation. • Evaluate CLDTrack on six benchmarks against 38 SOTA trackers.
Keywords:
Multi-modal fusion
Vision–Language Models (VLMs)
Visual Object Tracking (VOT)
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15.5
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4.3K
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