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Simply translating symbolic sign language notations into natural language unlocks significantly better motion generation when conditioning on phonological attributes with CLIP.
Gesture-aware pretraining unlocks significant improvements in 3D hand pose estimation, proving that semantic gesture information acts as a powerful inductive bias.
Achieve competitive video generation with Stable Diffusion using only 2.9% additional parameters by adapting temporal attention based on motion content, outperforming methods with explicit temporal consistency losses.
