SAMoR encodes motions of arbitrary skeletons into a fixed set of 8 part tokens via graph-transformer encoding, cross-attention pooling, and residual vector quantization, enabling cross-topology reconstruction, transfer, and text-conditioned generation.
Executing your commands via motion diffusion in latent space
3 Pith papers cite this work. Polarity classification is still indexing.
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ViBES introduces a speech-language-behavior model using modality-specific transformer experts that jointly generates dialogue and 3D body actions, showing gains over separate co-speech and text-to-motion baselines on multi-turn metrics.
FactorizedHMR recovers 3D human meshes from video by deterministically anchoring the torso-root then probabilistically completing distal articulations via flow-matching with geometry-aware supervision and a synthetic data pipeline.
citing papers explorer
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SAMoR: Motion Modelling for Articulated Objects of Any Skeleton and Topology
SAMoR encodes motions of arbitrary skeletons into a fixed set of 8 part tokens via graph-transformer encoding, cross-attention pooling, and residual vector quantization, enabling cross-topology reconstruction, transfer, and text-conditioned generation.
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ViBES: A Conversational Agent with Behaviorally-Intelligent 3D Virtual Body
ViBES introduces a speech-language-behavior model using modality-specific transformer experts that jointly generates dialogue and 3D body actions, showing gains over separate co-speech and text-to-motion baselines on multi-turn metrics.
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FactorizedHMR: A Hybrid Framework for Video Human Mesh Recovery
FactorizedHMR recovers 3D human meshes from video by deterministically anchoring the torso-root then probabilistically completing distal articulations via flow-matching with geometry-aware supervision and a synthetic data pipeline.