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Grounding motion predictions in 3D spatial context and language leads to significantly more accurate and coherent forecasts of human actions.
RAHA achieves superior cross-modal retrieval performance by leveraging hyperbolic geometry to better capture the low-dimensional semantics of image-text pairs.
