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Imperial College London
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Synthesizing realistic hand-object interactions is now possible with HO-Flow, a framework that leverages masked flow matching and interaction-aware VAEs to achieve state-of-the-art results in motion diversity and physical plausibility.
MLLMs can now better understand your pointing with Hand Intent Tokens (HINT), boosting accuracy on egocentric video question answering by 6.6% on a new benchmark.
Unlock scalable CAD generation from unannotated 3D meshes with DreamCAD, a framework that directly produces editable BREPs from point-level supervision, outperforming existing methods and achieving over 75% user preference.