CoAMD unifies skeleton-based action recognition and text-to-motion generation through autoregressive diffusion guided by a multi-modal recognizer, reporting SOTA results on 13 benchmarks for four tasks.
Tm2t: Stochastic and tokenized modeling for the reciprocal genera- tion of 3d human motions and texts
3 Pith papers cite this work. Polarity classification is still indexing.
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PolySLGen generates contextually appropriate and temporally coherent multimodal speaking and listening reactions for polyadic interactions by fusing group motion and social cues.
PhysiGen reduces interpenetration in text-driven 3D human interaction generation by simplifying meshes to geometric primitives for fast collision detection and guiding optimization with collision regions.
citing papers explorer
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Marrying Text-to-Motion Generation with Skeleton-Based Action Recognition
CoAMD unifies skeleton-based action recognition and text-to-motion generation through autoregressive diffusion guided by a multi-modal recognizer, reporting SOTA results on 13 benchmarks for four tasks.
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PolySLGen: Online Multimodal Speaking-Listening Reaction Generation in Polyadic Interaction
PolySLGen generates contextually appropriate and temporally coherent multimodal speaking and listening reactions for polyadic interactions by fusing group motion and social cues.
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PhysiGen: Integrating Collision-Aware Physical Constraints for High-Fidelity Human-Human Interaction Generation
PhysiGen reduces interpenetration in text-driven 3D human interaction generation by simplifying meshes to geometric primitives for fast collision detection and guiding optimization with collision regions.