A latent diffusion model over continuous implicit neural representations samples INR parameters from sparse keyframes to reconstruct plausible, smooth, and diverse motions while preserving keyframe accuracy.
Generating diverse and natural 3d human motions from text,
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2026 2verdicts
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Motion-Adapter improves text-to-motion diffusion models for compound actions by using decoupled cross-attention maps as structural masks during denoising to produce more coherent full-body motions.
citing papers explorer
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Generative Motion In-betweening by Diffusion over Continuous Implicit Representations
A latent diffusion model over continuous implicit neural representations samples INR parameters from sparse keyframes to reconstruct plausible, smooth, and diverse motions while preserving keyframe accuracy.
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Motion-Adapter: A Diffusion Model Adapter for Text-to-Motion Generation of Compound Actions
Motion-Adapter improves text-to-motion diffusion models for compound actions by using decoupled cross-attention maps as structural masks during denoising to produce more coherent full-body motions.