Retrieval from motion datasets combined with LLM task parsing and reward-guided noise initialization enables training-free diffusion optimization to satisfy severe spatiotemporal constraints in human motion generation.
Smpl: A skinned multi- person linear model.ACM Transactions on Graphics, 34(6)
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A Transformer model with unified skeleton representation, two-stream motion encoder, and multi-grained motion-text contrastive alignment achieves effective recognition on a new integrated heterogeneous open-vocabulary skeleton dataset.
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Towards Highly-Constrained Human Motion Generation with Retrieval-Guided Diffusion Noise Optimization
Retrieval from motion datasets combined with LLM task parsing and reward-guided noise initialization enables training-free diffusion optimization to satisfy severe spatiotemporal constraints in human motion generation.
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Towards Universal Skeleton-Based Action Recognition
A Transformer model with unified skeleton representation, two-stream motion encoder, and multi-grained motion-text contrastive alignment achieves effective recognition on a new integrated heterogeneous open-vocabulary skeleton dataset.