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Hierarchical supervision from RGB models can significantly boost depth estimation accuracy in thermal imaging, even in adverse conditions.
Hierarchical alignment of standardized embeddings can significantly enhance zero-shot learning performance by addressing the inherent mismatches between audio-visual and textual modalities.
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